data
dict |
|---|
{
"issue": {
"id": "1y2FkV9ZFKM",
"title": "Nov.",
"year": "2021",
"issueNum": "11",
"idPrefix": "tg",
"pubType": "journal",
"volume": "27",
"label": "Nov.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1wpqBpgOKUE",
"doi": "10.1109/TVCG.2021.3106501",
"abstract": "In this paper, we propose a novel redirected walking (RDW) technique that applies dynamic bending and curvature gains so that users perceive less discomfort than existing techniques that apply constant gains. Humans are less likely to notice continuous changes than those that are sudden. Therefore, instead of applying constant bending or curvature gains to users, we propose a dynamic method that continuously changes the gains. We conduct experiments to investigate the effect of dynamic gains in bending and curvature manipulation with regards to discomfort. The experimental results show that the proposed method significantly suppresses discomfort by up to 16 and 9% for bending and curvature manipulations, respectively.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In this paper, we propose a novel redirected walking (RDW) technique that applies dynamic bending and curvature gains so that users perceive less discomfort than existing techniques that apply constant gains. Humans are less likely to notice continuous changes than those that are sudden. Therefore, instead of applying constant bending or curvature gains to users, we propose a dynamic method that continuously changes the gains. We conduct experiments to investigate the effect of dynamic gains in bending and curvature manipulation with regards to discomfort. The experimental results show that the proposed method significantly suppresses discomfort by up to 16 and 9% for bending and curvature manipulations, respectively.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In this paper, we propose a novel redirected walking (RDW) technique that applies dynamic bending and curvature gains so that users perceive less discomfort than existing techniques that apply constant gains. Humans are less likely to notice continuous changes than those that are sudden. Therefore, instead of applying constant bending or curvature gains to users, we propose a dynamic method that continuously changes the gains. We conduct experiments to investigate the effect of dynamic gains in bending and curvature manipulation with regards to discomfort. The experimental results show that the proposed method significantly suppresses discomfort by up to 16 and 9% for bending and curvature manipulations, respectively.",
"title": "Redirected Walking using Continuous Curvature Manipulation",
"normalizedTitle": "Redirected Walking using Continuous Curvature Manipulation",
"fno": "09523890",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Bending",
"Road Safety",
"Road Vehicles",
"Virtual Reality",
"Curvature Gains",
"Dynamic Gains",
"Bending Curvature Manipulation",
"Continuous Curvature Manipulation",
"Redirected Walking Technique",
"Dynamic Bending",
"Constant Bending",
"Legged Locomotion",
"Bending",
"Manipulator Dynamics",
"Trajectory",
"Information Science",
"Visualization",
"Virtual Environments",
"Redirected Walking",
"Continuous Curvature Change",
"Dynamic Gain",
"Clothoid Curve",
"Virtual Reality"
],
"authors": [
{
"givenName": "Hiroaki",
"surname": "Sakono",
"fullName": "Hiroaki Sakono",
"affiliation": "Graduate School of Information Science and Technology, the University of Tokyo, Tokyo, Japan",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Keigo",
"surname": "Matsumoto",
"fullName": "Keigo Matsumoto",
"affiliation": "Graduate School of Information Science and Technology, the University of Tokyo, Tokyo, Japan",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Takuji",
"surname": "Narumi",
"fullName": "Takuji Narumi",
"affiliation": "Graduate School of Information Science and Technology, the University of Tokyo, Tokyo, Japan",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Hideaki",
"surname": "Kuzuoka",
"fullName": "Hideaki Kuzuoka",
"affiliation": "Graduate School of Information Science and Technology, the University of Tokyo, Tokyo, Japan",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": false,
"showRecommendedArticles": true,
"isOpenAccess": true,
"issueNum": "11",
"pubDate": "2021-11-01 00:00:00",
"pubType": "trans",
"pages": "4278-4288",
"year": "2021",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/vr/2017/6647/0/07892279",
"title": "Curvature gains in redirected walking: A closer look",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2017/07892279/12OmNBEGYJE",
"parentPublication": {
"id": "proceedings/vr/2017/6647/0",
"title": "2017 IEEE Virtual Reality (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2018/3365/0/08446479",
"title": "Adopting the Roll Manipulation for Redirected Walking",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2018/08446479/13bd1eSlys4",
"parentPublication": {
"id": "proceedings/vr/2018/3365/0",
"title": "2018 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2018/3365/0/08446062",
"title": "Biomechanical Parameters Under Curvature Gains and Bending Gains in Redirected Walking",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2018/08446062/13bd1fKQxrR",
"parentPublication": {
"id": "proceedings/vr/2018/3365/0",
"title": "2018 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2018/3365/0/08446225",
"title": "Effect of Environment Size on Curvature Redirected Walking Thresholds",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2018/08446225/13bd1sx4Zt8",
"parentPublication": {
"id": "proceedings/vr/2018/3365/0",
"title": "2018 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar/2018/7459/0/745900a115",
"title": "Rethinking Redirected Walking: On the Use of Curvature Gains Beyond Perceptual Limitations and Revisiting Bending Gains",
"doi": null,
"abstractUrl": "/proceedings-article/ismar/2018/745900a115/17D45WK5AlG",
"parentPublication": {
"id": "proceedings/ismar/2018/7459/0",
"title": "2018 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/05/08645699",
"title": "Shrinking Circles: Adaptation to Increased Curvature Gain in Redirected Walking",
"doi": null,
"abstractUrl": "/journal/tg/2019/05/08645699/17PYElBjW00",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2022/9617/0/961700a524",
"title": "The Chaotic Behavior of Redirection – Revisiting Simulations in Redirected Walking",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2022/961700a524/1CJc4FECUko",
"parentPublication": {
"id": "proceedings/vr/2022/9617/0",
"title": "2022 IEEE on Conference Virtual Reality and 3D User Interfaces (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/10049511",
"title": "Redirected Walking On Omnidirectional Treadmill",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/10049511/1KYoAYFd0m4",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2023/4815/0/481500a053",
"title": "Redirected Walking Based on Historical User Walking Data",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2023/481500a053/1MNgUnNG7Ju",
"parentPublication": {
"id": "proceedings/vr/2023/4815/0",
"title": "2023 IEEE Conference Virtual Reality and 3D User Interfaces (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar/2021/0158/0/015800a498",
"title": "Redirected Walking using Noisy Galvanic Vestibular Stimulation",
"doi": null,
"abstractUrl": "/proceedings-article/ismar/2021/015800a498/1yeCU92Xt5K",
"parentPublication": {
"id": "proceedings/ismar/2021/0158/0",
"title": "2021 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09523832",
"articleId": "1wpqjiNuSqY",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09523837",
"articleId": "1wpqBIpTeSs",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "1y2FkV9ZFKM",
"title": "Nov.",
"year": "2021",
"issueNum": "11",
"idPrefix": "tg",
"pubType": "journal",
"volume": "27",
"label": "Nov.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1wpqBIpTeSs",
"doi": "10.1109/TVCG.2021.3106507",
"abstract": "Target and steering-based techniques are two common approaches to travel in consumer VR applications. In this paper, we present two within-subject studies that employ a prior dual-task methodology to evaluate and compare the cognitive loads, travel performances, and simulator sickness of three common target-based travel techniques and three common steering-based travel techniques. We also present visual meta-analyses comparing our results to prior results using the same dual-task methodology. Based on our results and meta-analyses, we present several design suggestions for travel techniques based on various aspects of user experiences.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Target and steering-based techniques are two common approaches to travel in consumer VR applications. In this paper, we present two within-subject studies that employ a prior dual-task methodology to evaluate and compare the cognitive loads, travel performances, and simulator sickness of three common target-based travel techniques and three common steering-based travel techniques. We also present visual meta-analyses comparing our results to prior results using the same dual-task methodology. Based on our results and meta-analyses, we present several design suggestions for travel techniques based on various aspects of user experiences.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Target and steering-based techniques are two common approaches to travel in consumer VR applications. In this paper, we present two within-subject studies that employ a prior dual-task methodology to evaluate and compare the cognitive loads, travel performances, and simulator sickness of three common target-based travel techniques and three common steering-based travel techniques. We also present visual meta-analyses comparing our results to prior results using the same dual-task methodology. Based on our results and meta-analyses, we present several design suggestions for travel techniques based on various aspects of user experiences.",
"title": "The Cognitive Loads and Usability of Target-based and Steering-based Travel Techniques",
"normalizedTitle": "The Cognitive Loads and Usability of Target-based and Steering-based Travel Techniques",
"fno": "09523837",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Cognition",
"User Experience",
"Virtual Reality",
"Common Steering Based Travel Techniques",
"Dual Task Methodology",
"Cognitive Loads",
"Consumer VR Applications",
"Within Subject Studies",
"Travel Performances",
"Common Target Based Travel Techniques",
"Simulator Sickness",
"Visual Meta Analyses",
"User Experiences",
"Task Analysis",
"Visualization",
"Virtual Environments",
"Legged Locomotion",
"Buildings",
"Standards",
"Usability",
"Cognitive Load",
"3 D Travel Techniques",
"Virtual Reality"
],
"authors": [
{
"givenName": "Chengyuan",
"surname": "Lai",
"fullName": "Chengyuan Lai",
"affiliation": "University of Texas, Dallas, Richardson, TX, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Xinyu",
"surname": "Hu",
"fullName": "Xinyu Hu",
"affiliation": "University of Central Florida, Orlando, FL, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Afham Ahmed",
"surname": "Aiyaz",
"fullName": "Afham Ahmed Aiyaz",
"affiliation": "University of Texas, Dallas, Richardson, TX, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Ann",
"surname": "Segismundo",
"fullName": "Ann Segismundo",
"affiliation": "The Hockaday School, Dallas, TX, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Ananya",
"surname": "Phadke",
"fullName": "Ananya Phadke",
"affiliation": "The Hockaday School, Dallas, TX, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Ryan P.",
"surname": "McMahan",
"fullName": "Ryan P. McMahan",
"affiliation": "University of Central Florida, Orlando, FL, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "11",
"pubDate": "2021-11-01 00:00:00",
"pubType": "trans",
"pages": "4289-4299",
"year": "2021",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/snpd/2013/5005/0/5005a683",
"title": "System Architecture and Feature Design for Engineering a Web-Based Travel Advisor System: FanOnTour",
"doi": null,
"abstractUrl": "/proceedings-article/snpd/2013/5005a683/12OmNAnuTyQ",
"parentPublication": {
"id": "proceedings/snpd/2013/5005/0",
"title": "2013 14th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2014/2871/0/06802053",
"title": "An enhanced steering algorithm for redirected walking in virtual environments",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2014/06802053/12OmNCbU2Wt",
"parentPublication": {
"id": "proceedings/vr/2014/2871/0",
"title": "2014 IEEE Virtual Reality (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2017/6647/0/07892330",
"title": "Assisted travel based on common visibility and navigation meshes",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2017/07892330/12OmNqHItHv",
"parentPublication": {
"id": "proceedings/vr/2017/6647/0",
"title": "2017 IEEE Virtual Reality (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/3dui/2015/6886/0/07131766",
"title": "A multi-touch finger gesture based low-fatigue VR travel framework",
"doi": null,
"abstractUrl": "/proceedings-article/3dui/2015/07131766/12OmNzayNeN",
"parentPublication": {
"id": "proceedings/3dui/2015/6886/0",
"title": "2015 IEEE Symposium on 3D User Interfaces (3DUI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2017/6647/0/07892386",
"title": "Travel in large-scale head-worn VR: Pre-oriented teleportation with WIMs and previews",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2017/07892386/12OmNzhELm6",
"parentPublication": {
"id": "proceedings/vr/2017/6647/0",
"title": "2017 IEEE Virtual Reality (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2010/04/ttg2010040690",
"title": "Evaluation of the Cognitive Effects of Travel Technique in Complex Real and Virtual Environments",
"doi": null,
"abstractUrl": "/journal/tg/2010/04/ttg2010040690/13rRUIM2VGZ",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2019/1377/0/08798017",
"title": "Simulated Reference Frame Effects on Steering, Jumping and Sliding",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2019/08798017/1cJ0YUTkHao",
"parentPublication": {
"id": "proceedings/vr/2019/1377/0",
"title": "2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar-adjunct/2020/7675/0/767500a102",
"title": "The Comfort Benefits of Gaze-Directed Steering",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2020/767500a102/1pBMeQmOrAc",
"parentPublication": {
"id": "proceedings/ismar-adjunct/2020/7675/0",
"title": "2020 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar-adjunct/2020/7675/0/767500a074",
"title": "Locomotive and Cognitive Trade-Offs for Target-based Travel",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2020/767500a074/1pBMgcXhcOc",
"parentPublication": {
"id": "proceedings/ismar-adjunct/2020/7675/0",
"title": "2020 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar/2020/8508/0/850800a627",
"title": "The Cognitive Load and Usability of Three Walking Metaphors for Consumer Virtual Reality",
"doi": null,
"abstractUrl": "/proceedings-article/ismar/2020/850800a627/1pysyecdlzq",
"parentPublication": {
"id": "proceedings/ismar/2020/8508/0",
"title": "2020 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09523890",
"articleId": "1wpqBpgOKUE",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09523892",
"articleId": "1wpqm2ZIWTm",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "1y2FkV9ZFKM",
"title": "Nov.",
"year": "2021",
"issueNum": "11",
"idPrefix": "tg",
"pubType": "journal",
"volume": "27",
"label": "Nov.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1wpqm2ZIWTm",
"doi": "10.1109/TVCG.2021.3106504",
"abstract": "Virtual steering techniques enable users to navigate in larger Virtual Environments (VEs) than the physical workspace available. Even though these techniques do not require physical movement of the users (e.g. using a joystick and the head orientation to steer towards a virtual direction), recent work observed that users might unintentionally move in the physical workspace while navigating, resulting in Unintended Positional Drift (UPD). This phenomenon can be a safety issue since users may unintentionally reach the physical boundaries of the workspace while using a steering technique. In this context, as a necessary first step to improve the design of navigation techniques minimizing the UPD, this paper aims at analyzing and modeling the UPD during a virtual navigation task. In particular, we characterize and analyze the UPD for a dataset containing the positions and orientations of eighteen users performing a virtual slalom task using virtual steering techniques. Participants wore a head-mounted display and had to follow three different sinusoidal-like trajectories (with low, medium and high curvature) using a torso-steering navigation technique. We analyzed the performed motions and proposed two UPD models: the first based on a linear regression analysis and the second based on a Gaussian Mixture Model (GMM) analysis. Then, we assessed both models through a simulation-based evaluation where we reproduced the same navigation task using virtual agents. Our results indicate the feasibility of using simulation-based evaluations to study UPD. The paper concludes with a discussion of potential applications of the results in order to gain a better understanding of UPD during steering and therefore improve the design of navigation techniques by compensating for UPD.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Virtual steering techniques enable users to navigate in larger Virtual Environments (VEs) than the physical workspace available. Even though these techniques do not require physical movement of the users (e.g. using a joystick and the head orientation to steer towards a virtual direction), recent work observed that users might unintentionally move in the physical workspace while navigating, resulting in Unintended Positional Drift (UPD). This phenomenon can be a safety issue since users may unintentionally reach the physical boundaries of the workspace while using a steering technique. In this context, as a necessary first step to improve the design of navigation techniques minimizing the UPD, this paper aims at analyzing and modeling the UPD during a virtual navigation task. In particular, we characterize and analyze the UPD for a dataset containing the positions and orientations of eighteen users performing a virtual slalom task using virtual steering techniques. Participants wore a head-mounted display and had to follow three different sinusoidal-like trajectories (with low, medium and high curvature) using a torso-steering navigation technique. We analyzed the performed motions and proposed two UPD models: the first based on a linear regression analysis and the second based on a Gaussian Mixture Model (GMM) analysis. Then, we assessed both models through a simulation-based evaluation where we reproduced the same navigation task using virtual agents. Our results indicate the feasibility of using simulation-based evaluations to study UPD. The paper concludes with a discussion of potential applications of the results in order to gain a better understanding of UPD during steering and therefore improve the design of navigation techniques by compensating for UPD.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Virtual steering techniques enable users to navigate in larger Virtual Environments (VEs) than the physical workspace available. Even though these techniques do not require physical movement of the users (e.g. using a joystick and the head orientation to steer towards a virtual direction), recent work observed that users might unintentionally move in the physical workspace while navigating, resulting in Unintended Positional Drift (UPD). This phenomenon can be a safety issue since users may unintentionally reach the physical boundaries of the workspace while using a steering technique. In this context, as a necessary first step to improve the design of navigation techniques minimizing the UPD, this paper aims at analyzing and modeling the UPD during a virtual navigation task. In particular, we characterize and analyze the UPD for a dataset containing the positions and orientations of eighteen users performing a virtual slalom task using virtual steering techniques. Participants wore a head-mounted display and had to follow three different sinusoidal-like trajectories (with low, medium and high curvature) using a torso-steering navigation technique. We analyzed the performed motions and proposed two UPD models: the first based on a linear regression analysis and the second based on a Gaussian Mixture Model (GMM) analysis. Then, we assessed both models through a simulation-based evaluation where we reproduced the same navigation task using virtual agents. Our results indicate the feasibility of using simulation-based evaluations to study UPD. The paper concludes with a discussion of potential applications of the results in order to gain a better understanding of UPD during steering and therefore improve the design of navigation techniques by compensating for UPD.",
"title": "Understanding, Modeling and Simulating Unintended Positional Drift during Repetitive Steering Navigation Tasks in Virtual Reality",
"normalizedTitle": "Understanding, Modeling and Simulating Unintended Positional Drift during Repetitive Steering Navigation Tasks in Virtual Reality",
"fno": "09523892",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Gaussian Processes",
"Helmet Mounted Displays",
"Interactive Devices",
"Regression Analysis",
"Virtual Reality",
"Virtual Agents",
"Simulation Based Evaluation",
"Navigation Techniques",
"Repetitive Steering Navigation Tasks",
"Virtual Reality",
"Virtual Steering Techniques",
"Larger Virtual Environments",
"Physical Workspace",
"Physical Movement",
"Virtual Direction",
"Unintended Positional Drift",
"Physical Boundaries",
"Steering Technique",
"Virtual Navigation Task",
"Eighteen Users",
"Virtual Slalom Task",
"Torso Steering Navigation Technique",
"UPD Models",
"Gaussian Mixture Model Analysis",
"Visualization",
"Virtual Reality",
"Navigation",
"Steering Techniques",
"Motion Analysis"
],
"authors": [
{
"givenName": "Hugo",
"surname": "Brument",
"fullName": "Hugo Brument",
"affiliation": "Univ. Rennes, Inria, IRISA, France",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Gerd",
"surname": "Bruder",
"fullName": "Gerd Bruder",
"affiliation": "University of Central Florida, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Maud",
"surname": "Marchal",
"fullName": "Maud Marchal",
"affiliation": "Univ. Rennes, INSA, IRISA, Inria, CNRS - France and IUF, France",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Anne Hélène",
"surname": "Olivier",
"fullName": "Anne Hélène Olivier",
"affiliation": "Univ Rennes, Inria, CNRS, IRISA, M2S, Rennes, France",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Ferran",
"surname": "Argelaguet",
"fullName": "Ferran Argelaguet",
"affiliation": "Inria, Univ. Rennes, CNRS, IRISA, France",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "11",
"pubDate": "2021-11-01 00:00:00",
"pubType": "trans",
"pages": "4300-4310",
"year": "2021",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/vr/2014/2871/0/06802071",
"title": "A comparison of four different approaches to reducing unintended positional drift during walking-In-Place locomotion",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2014/06802071/12OmNqzu6Ve",
"parentPublication": {
"id": "proceedings/vr/2014/2871/0",
"title": "2014 IEEE Virtual Reality (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/3dui/2014/3624/0/06798850",
"title": "A comparison of different methods for reducing the unintended positional drift accompanying walking-in-place locomotion",
"doi": null,
"abstractUrl": "/proceedings-article/3dui/2014/06798850/12OmNvCzFbu",
"parentPublication": {
"id": "proceedings/3dui/2014/3624/0",
"title": "2014 IEEE Symposium on 3D User Interfaces (3DUI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2017/6647/0/07892348",
"title": "Steering locomotion by vestibular perturbation in room-scale VR",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2017/07892348/12OmNvrMUgU",
"parentPublication": {
"id": "proceedings/vr/2017/6647/0",
"title": "2017 IEEE Virtual Reality (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2013/4795/0/06549392",
"title": "Unintended positional drift and its potential solutions",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2013/06549392/12OmNxXCGFc",
"parentPublication": {
"id": "proceedings/vr/2013/4795/0",
"title": "2013 IEEE Virtual Reality (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/haptics/2002/1489/0/14890352",
"title": "Haptic Interface for Center-of-Workspace Interaction",
"doi": null,
"abstractUrl": "/proceedings-article/haptics/2002/14890352/12OmNzTppyy",
"parentPublication": {
"id": "proceedings/haptics/2002/1489/0",
"title": "Haptic Interfaces for Virtual Environment and Teleoperator Systems, International Symposium on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2015/1727/0/07223323",
"title": "User cohabitation in multi-stereoscopic immersive virtual environment for individual navigation tasks",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2015/07223323/12OmNzZmZu4",
"parentPublication": {
"id": "proceedings/vr/2015/1727/0",
"title": "2015 IEEE Virtual Reality (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2013/12/ttg2013122207",
"title": "The Impact of Physical Navigation on Spatial Organization for Sensemaking",
"doi": null,
"abstractUrl": "/journal/tg/2013/12/ttg2013122207/13rRUwI5TQZ",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2022/9617/0/961700a674",
"title": "Virtual Workspace Positioning Techniques during Teleportation for Co-located Collaboration in Virtual Reality using HMDs",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2022/961700a674/1CJbVNhPGSI",
"parentPublication": {
"id": "proceedings/vr/2022/9617/0",
"title": "2022 IEEE on Conference Virtual Reality and 3D User Interfaces (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2019/1377/0/08797980",
"title": "Exploring Scalable WorkSpace Based on Virtual and Physical Movable Wall",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2019/08797980/1cJ14PgErfi",
"parentPublication": {
"id": "proceedings/vr/2019/1377/0",
"title": "2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sibgrapi/2020/9274/0/927400a031",
"title": "Towards a Legion of Virtual Humans: Steering Behaviors and Organic Visualization",
"doi": null,
"abstractUrl": "/proceedings-article/sibgrapi/2020/927400a031/1p2VyqWyw92",
"parentPublication": {
"id": "proceedings/sibgrapi/2020/9274/0",
"title": "2020 33rd SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09523837",
"articleId": "1wpqBIpTeSs",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09523835",
"articleId": "1wpqlnY7sje",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1y2Fo9FTtyo",
"name": "ttg202111-09523892s1-supp1-3106504.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202111-09523892s1-supp1-3106504.mp4",
"extension": "mp4",
"size": "9.51 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1y2FkV9ZFKM",
"title": "Nov.",
"year": "2021",
"issueNum": "11",
"idPrefix": "tg",
"pubType": "journal",
"volume": "27",
"label": "Nov.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1wpqlnY7sje",
"doi": "10.1109/TVCG.2021.3106476",
"abstract": "Work on VR and AR task interaction and visualization paradigms has typically focused on providing information about the current step (a cue) immediately before or during its performance. Some research has also shown benefits to simultaneously providing information about the next step (a precue). We explore whether it would be possible to improve efficiency by precueing information about multiple upcoming steps before completing the current step. To accomplish this, we developed a remote VR user study comparing task completion time and subjective metrics for different levels and styles of precueing in a path-following task. Our visualizations vary the precueing level (number of steps precued in advance) and style (whether the path to a target is communicated through a line to the target, and whether the place of a target is communicated through graphics at the target). Participants in our study performed best when given two to three precues for visualizations using lines to show the path to targets. However, performance degraded when four precues were used. On the other hand, participants performed best with only one precue for visualizations without lines, showing only the places of targets, and performance degraded when a second precue was given. In addition, participants performed better using visualizations with lines than ones without lines.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Work on VR and AR task interaction and visualization paradigms has typically focused on providing information about the current step (a cue) immediately before or during its performance. Some research has also shown benefits to simultaneously providing information about the next step (a precue). We explore whether it would be possible to improve efficiency by precueing information about multiple upcoming steps before completing the current step. To accomplish this, we developed a remote VR user study comparing task completion time and subjective metrics for different levels and styles of precueing in a path-following task. Our visualizations vary the precueing level (number of steps precued in advance) and style (whether the path to a target is communicated through a line to the target, and whether the place of a target is communicated through graphics at the target). Participants in our study performed best when given two to three precues for visualizations using lines to show the path to targets. However, performance degraded when four precues were used. On the other hand, participants performed best with only one precue for visualizations without lines, showing only the places of targets, and performance degraded when a second precue was given. In addition, participants performed better using visualizations with lines than ones without lines.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Work on VR and AR task interaction and visualization paradigms has typically focused on providing information about the current step (a cue) immediately before or during its performance. Some research has also shown benefits to simultaneously providing information about the next step (a precue). We explore whether it would be possible to improve efficiency by precueing information about multiple upcoming steps before completing the current step. To accomplish this, we developed a remote VR user study comparing task completion time and subjective metrics for different levels and styles of precueing in a path-following task. Our visualizations vary the precueing level (number of steps precued in advance) and style (whether the path to a target is communicated through a line to the target, and whether the place of a target is communicated through graphics at the target). Participants in our study performed best when given two to three precues for visualizations using lines to show the path to targets. However, performance degraded when four precues were used. On the other hand, participants performed best with only one precue for visualizations without lines, showing only the places of targets, and performance degraded when a second precue was given. In addition, participants performed better using visualizations with lines than ones without lines.",
"title": "Using Multi-Level Precueing to Improve Performance in Path-Following Tasks in Virtual Reality",
"normalizedTitle": "Using Multi-Level Precueing to Improve Performance in Path-Following Tasks in Virtual Reality",
"fno": "09523835",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Augmented Reality",
"Data Visualisation",
"Multilevel Precueing",
"Path Following Task",
"Visualization Paradigms",
"Remote VR User Study",
"Task Completion Time",
"Virtual Reality",
"AR Task Interaction",
"Visualization",
"Task Analysis",
"Performance Evaluation",
"Games",
"Virtual Environments",
"Feedforward Systems",
"Computer Science",
"Virtual Reality",
"Path Following",
"Visual Cues",
"Task Precueing",
"Remote VR User Study"
],
"authors": [
{
"givenName": "Jen-Shuo",
"surname": "Liu",
"fullName": "Jen-Shuo Liu",
"affiliation": "Department of Computer Science, Columbia University, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Carmine",
"surname": "Elvezio",
"fullName": "Carmine Elvezio",
"affiliation": "Department of Computer Science, Columbia University, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Barbara",
"surname": "Tversky",
"fullName": "Barbara Tversky",
"affiliation": "Department of Human Development, Teachers College, Columbia University, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Steven",
"surname": "Feiner",
"fullName": "Steven Feiner",
"affiliation": "Department of Computer Science, Columbia University, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "11",
"pubDate": "2021-11-01 00:00:00",
"pubType": "trans",
"pages": "4311-4320",
"year": "2021",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/itag/2014/6795/0/6795a013",
"title": "How Body Movement Influences Virtual Reality Analgesia?",
"doi": null,
"abstractUrl": "/proceedings-article/itag/2014/6795a013/12OmNC4wtBe",
"parentPublication": {
"id": "proceedings/itag/2014/6795/0",
"title": "2014 International Conference on Interactive Technologies and Games (iTAG)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismarw/2016/3740/0/07836491",
"title": "Using Visual Effects to Facilitate Depth Perception for Spatial Tasks in Virtual and Augmented Reality",
"doi": null,
"abstractUrl": "/proceedings-article/ismarw/2016/07836491/12OmNwdtw9P",
"parentPublication": {
"id": "proceedings/ismarw/2016/3740/0",
"title": "2016 IEEE International Symposium on Mixed and Augmented Reality (ISMAR-Adjunct)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2016/0836/0/07504761",
"title": "Avatar realism and social interaction quality in virtual reality",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2016/07504761/12OmNzdoMvk",
"parentPublication": {
"id": "proceedings/vr/2016/0836/0",
"title": "2016 IEEE Virtual Reality (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2022/9617/0/961700a330",
"title": "Investigating the Effects of Leading and Following Behaviors of Virtual Humans in Collaborative Fine Motor Tasks in Virtual Reality",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2022/961700a330/1CJc2ZgMCFq",
"parentPublication": {
"id": "proceedings/vr/2022/9617/0",
"title": "2022 IEEE on Conference Virtual Reality and 3D User Interfaces (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2023/4815/0/481500a152",
"title": "Comparing Visual Attention with Leading and Following Virtual Agents in a Collaborative Perception-Action Task in VR",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2023/481500a152/1MNgPjLVSUg",
"parentPublication": {
"id": "proceedings/vr/2023/4815/0",
"title": "2023 IEEE Conference Virtual Reality and 3D User Interfaces (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2019/1377/0/08798348",
"title": "Individual Differences in Embodied Distance Estimation in Virtual Reality",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2019/08798348/1cJ0H4fRjBS",
"parentPublication": {
"id": "proceedings/vr/2019/1377/0",
"title": "2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2019/1377/0/08797870",
"title": "The Influence of Body Position on Presence When Playing a Virtual Reality Game",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2019/08797870/1cJ0RyhQnC0",
"parentPublication": {
"id": "proceedings/vr/2019/1377/0",
"title": "2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2019/1377/0/08798095",
"title": "Distance Judgments to On- and Off-Ground Objects in Augmented Reality",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2019/08798095/1cJ0Yxz6rrG",
"parentPublication": {
"id": "proceedings/vr/2019/1377/0",
"title": "2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/massw/2019/4121/0/412100a072",
"title": "Cognitive Distraction to Improve Cybersickness in Virtual Reality Environment",
"doi": null,
"abstractUrl": "/proceedings-article/massw/2019/412100a072/1iTvAIC4RJ6",
"parentPublication": {
"id": "proceedings/massw/2019/4121/0",
"title": "2019 IEEE 16th International Conference on Mobile Ad Hoc and Sensor Systems Workshops (MASSW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vl-hcc/2021/4592/0/09576317",
"title": "Travel Kinematics in Virtual Reality Increases Learning Efficiency",
"doi": null,
"abstractUrl": "/proceedings-article/vl-hcc/2021/09576317/1y63qGwvZ16",
"parentPublication": {
"id": "proceedings/vl-hcc/2021/4592/0",
"title": "2021 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09523892",
"articleId": "1wpqm2ZIWTm",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09523893",
"articleId": "1wpqC4BIYla",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1y5Zaz0suEo",
"name": "ttg202111-09523835s1-tvcg-3106476-mm.zip",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202111-09523835s1-tvcg-3106476-mm.zip",
"extension": "zip",
"size": "66 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1y2FkV9ZFKM",
"title": "Nov.",
"year": "2021",
"issueNum": "11",
"idPrefix": "tg",
"pubType": "journal",
"volume": "27",
"label": "Nov.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1wpqC4BIYla",
"doi": "10.1109/TVCG.2021.3106490",
"abstract": "360-degree experiences such as cinematic virtual reality and 360-degree videos are becoming increasingly popular. In most examples, viewers can freely explore the content by changing their orientation. However, in some cases, this increased freedom may lead to viewers missing important events within such experiences. Thus, a recent research thrust has focused on studying mechanisms for guiding viewers' attention while maintaining their sense of presence and fostering a positive user experience. One approach is the utilization of diegetic mechanisms, characterized by an internal consistency with respect to the narrative and the environment, for attention guidance. While such mechanisms are highly attractive, their uses and potential implementations are still not well understood. Additionally, acknowledging the user in 360-degree experiences has been linked to a higher sense of presence and connection. However, less is known when acknowledging behaviors are carried out by attention guiding mechanisms. To close these gaps, we conducted a within-subjects user study with five conditions of no guide and virtual arrows, birds, dogs, and dogs that acknowledge the user and the environment. Through our mixed-methods analysis, we found that the diegetic virtual animals resulted in a more positive user experience, all of which were at least as effective as the non-diegetic arrow in guiding users towards target events. The acknowledging dog received the most positive responses from our participants in terms of preference and user experience and significantly improved their sense of presence compared to the non-diegetic arrow. Lastly, three themes emerged from a qualitative analysis of our participants' feedback, indicating the importance of the guide's blending in, its acknowledging behavior, and participants' positive associations as the main factors for our participants' preferences.",
"abstracts": [
{
"abstractType": "Regular",
"content": "360-degree experiences such as cinematic virtual reality and 360-degree videos are becoming increasingly popular. In most examples, viewers can freely explore the content by changing their orientation. However, in some cases, this increased freedom may lead to viewers missing important events within such experiences. Thus, a recent research thrust has focused on studying mechanisms for guiding viewers' attention while maintaining their sense of presence and fostering a positive user experience. One approach is the utilization of diegetic mechanisms, characterized by an internal consistency with respect to the narrative and the environment, for attention guidance. While such mechanisms are highly attractive, their uses and potential implementations are still not well understood. Additionally, acknowledging the user in 360-degree experiences has been linked to a higher sense of presence and connection. However, less is known when acknowledging behaviors are carried out by attention guiding mechanisms. To close these gaps, we conducted a within-subjects user study with five conditions of no guide and virtual arrows, birds, dogs, and dogs that acknowledge the user and the environment. Through our mixed-methods analysis, we found that the diegetic virtual animals resulted in a more positive user experience, all of which were at least as effective as the non-diegetic arrow in guiding users towards target events. The acknowledging dog received the most positive responses from our participants in terms of preference and user experience and significantly improved their sense of presence compared to the non-diegetic arrow. Lastly, three themes emerged from a qualitative analysis of our participants' feedback, indicating the importance of the guide's blending in, its acknowledging behavior, and participants' positive associations as the main factors for our participants' preferences.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "360-degree experiences such as cinematic virtual reality and 360-degree videos are becoming increasingly popular. In most examples, viewers can freely explore the content by changing their orientation. However, in some cases, this increased freedom may lead to viewers missing important events within such experiences. Thus, a recent research thrust has focused on studying mechanisms for guiding viewers' attention while maintaining their sense of presence and fostering a positive user experience. One approach is the utilization of diegetic mechanisms, characterized by an internal consistency with respect to the narrative and the environment, for attention guidance. While such mechanisms are highly attractive, their uses and potential implementations are still not well understood. Additionally, acknowledging the user in 360-degree experiences has been linked to a higher sense of presence and connection. However, less is known when acknowledging behaviors are carried out by attention guiding mechanisms. To close these gaps, we conducted a within-subjects user study with five conditions of no guide and virtual arrows, birds, dogs, and dogs that acknowledge the user and the environment. Through our mixed-methods analysis, we found that the diegetic virtual animals resulted in a more positive user experience, all of which were at least as effective as the non-diegetic arrow in guiding users towards target events. The acknowledging dog received the most positive responses from our participants in terms of preference and user experience and significantly improved their sense of presence compared to the non-diegetic arrow. Lastly, three themes emerged from a qualitative analysis of our participants' feedback, indicating the importance of the guide's blending in, its acknowledging behavior, and participants' positive associations as the main factors for our participants' preferences.",
"title": "Virtual Animals as Diegetic Attention Guidance Mechanisms in 360-Degree Experiences",
"normalizedTitle": "Virtual Animals as Diegetic Attention Guidance Mechanisms in 360-Degree Experiences",
"fno": "09523893",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Cameras",
"Computer Animation",
"Human Computer Interaction",
"User Experience",
"Video Signal Processing",
"Virtual Reality",
"360 Degree Videos",
"Positive User Experience",
"360 Degree Experiences",
"Acknowledging Behavior",
"Attention Guiding Mechanisms",
"Virtual Arrows",
"Diegetic Virtual Animals",
"Nondiegetic Arrow",
"Diegetic Attention Guidance Mechanisms",
"Cinematic Virtual Reality",
"User Experience",
"Dogs",
"Birds",
"Videos",
"Three Dimensional Displays",
"Computational Modeling",
"Virtual Environments",
"Virtual Reality",
"360 Degree Experiences",
"Attention Guidance",
"Diegetic Cues",
"Virtual Animals"
],
"authors": [
{
"givenName": "Nahal",
"surname": "Norouzi",
"fullName": "Nahal Norouzi",
"affiliation": "University of Central Florida, Orlando, FL, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Gerd",
"surname": "Bruder",
"fullName": "Gerd Bruder",
"affiliation": "University of Central Florida, Orlando, FL, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Austin",
"surname": "Erickson",
"fullName": "Austin Erickson",
"affiliation": "University of Central Florida, Orlando, FL, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Kangsoo",
"surname": "Kim",
"fullName": "Kangsoo Kim",
"affiliation": "University of Calgary, Calgary, Canada",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jeremy",
"surname": "Bailenson",
"fullName": "Jeremy Bailenson",
"affiliation": "Stanford University, Stanford, CA, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Pamela",
"surname": "Wisniewski",
"fullName": "Pamela Wisniewski",
"affiliation": "University of Central Florida, Orlando, FL, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Charlie",
"surname": "Hughes",
"fullName": "Charlie Hughes",
"affiliation": "University of Central Florida, Orlando, FL, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Greg",
"surname": "Welch",
"fullName": "Greg Welch",
"affiliation": "University of Central Florida, Orlando, FL, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "11",
"pubDate": "2021-11-01 00:00:00",
"pubType": "trans",
"pages": "4321-4331",
"year": "2021",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/icme/2018/1737/0/08486537",
"title": "A Subjective Study of Viewer Navigation Behaviors When Watching 360-Degree Videos on Computers",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2018/08486537/14jQfTvagGm",
"parentPublication": {
"id": "proceedings/icme/2018/1737/0",
"title": "2018 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/lcn/2018/4413/0/08638092",
"title": "Plato: Learning-based Adaptive Streaming of 360-Degree Videos",
"doi": null,
"abstractUrl": "/proceedings-article/lcn/2018/08638092/18rqIpj1b3i",
"parentPublication": {
"id": "proceedings/lcn/2018/4413/0",
"title": "2018 IEEE 43rd Conference on Local Computer Networks (LCN)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/05/10053631",
"title": "Introducing 3D Thumbnails to Access 360-Degree Videos in Virtual Reality",
"doi": null,
"abstractUrl": "/journal/tg/2023/05/10053631/1L1HXLrXmqA",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/percom-workshops/2019/9151/0/08730763",
"title": "Proposal of a Spherical Heat Map in 360-Degree Internet Live Broadcasting Using Viewers' POV",
"doi": null,
"abstractUrl": "/proceedings-article/percom-workshops/2019/08730763/1aDSGhosaR2",
"parentPublication": {
"id": "proceedings/percom-workshops/2019/9151/0",
"title": "2019 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2019/1377/0/08797753",
"title": "Sustainable Production and Consumption in 360",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2019/08797753/1cJ0PXmlWZW",
"parentPublication": {
"id": "proceedings/vr/2019/1377/0",
"title": "2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2019/2838/0/283800a081",
"title": "User Experience Study of 360° Music Videos on Computer Monitor and Virtual Reality Goggles",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2019/283800a081/1cMFaY4kg6I",
"parentPublication": {
"id": "proceedings/iv/2019/2838/0",
"title": "2019 23rd International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ifip-networking/2019/16/0/08999460",
"title": "Advancing user quality of experience in 360-degree video streaming",
"doi": null,
"abstractUrl": "/proceedings-article/ifip-networking/2019/08999460/1hHLyJf1thC",
"parentPublication": {
"id": "proceedings/ifip-networking/2019/16/0",
"title": "2019 IFIP Networking Conference (IFIP Networking)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/searis/2018/6272/0/09180230",
"title": "Lightweight Visualization and User Logging for Mobile 360-degree Videos",
"doi": null,
"abstractUrl": "/proceedings-article/searis/2018/09180230/1mK7jepaiRy",
"parentPublication": {
"id": "proceedings/searis/2018/6272/0",
"title": "2018 IEEE 11th Workshop on Software Engineering and Architectures for Real-time Interactive Systems (SEARIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar/2020/8508/0/850800a600",
"title": "Automatic Generation of Diegetic Guidance in Cinematic Virtual Reality",
"doi": null,
"abstractUrl": "/proceedings-article/ismar/2020/850800a600/1pysw9jL61i",
"parentPublication": {
"id": "proceedings/ismar/2020/8508/0",
"title": "2020 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ism/2020/8697/0/869700a082",
"title": "Redefine the A in ABR for 360-degree Videos: A Flexible ABR Framework",
"doi": null,
"abstractUrl": "/proceedings-article/ism/2020/869700a082/1qBbIEON8UU",
"parentPublication": {
"id": "proceedings/ism/2020/8697/0",
"title": "2020 IEEE International Symposium on Multimedia (ISM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09523835",
"articleId": "1wpqlnY7sje",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09523839",
"articleId": "1wpqu0pXouA",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "1y2FkV9ZFKM",
"title": "Nov.",
"year": "2021",
"issueNum": "11",
"idPrefix": "tg",
"pubType": "journal",
"volume": "27",
"label": "Nov.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1wpqu0pXouA",
"doi": "10.1109/TVCG.2021.3106506",
"abstract": "Instrument alignment is a common task in various surgical interventions using navigation. The goal of the task is to position and orient an instrument as it has been planned preoperatively. To this end, surgeons rely on patient-specific data visualized on screens alongside preplanned trajectories. The purpose of this manuscript is to investigate the effect of instrument visualization/non visualization on alignment tasks, and to compare it with virtual extensions approach which augments the realistic representation of the instrument with simple 3D objects. 18 volunteers performed six alignment tasks under each of the following conditions: no visualization on the instrument; realistic visualization of the instrument; realistic visualization extended with virtual elements (Virtual extensions). The first condition represents an egocentric-based alignment while the two other conditions additionally make use of exocentric depth estimation to perform the alignment. The device used was a see-through device (Microsoft HoloLens 2). The positions of the head and the instrument were acquired during the experiment. Additionally, the users were asked to fill NASA-TLX and SUS forms for each condition. The results show that instrument visualization is essential for a good alignment using see-through devices. Moreover, virtual extensions helped achieve the best performance compared to the other conditions with medians of 2 <italic>mm</italic> and 2° positional and angular error respectively. Furthermore, the virtual extensions decreased the average head velocity while similarly reducing the frustration levels. Therefore, making use of virtual extensions could facilitate alignment tasks in augmented and virtual reality (AR/VR) environments, specifically in AR navigated surgical procedures when using optical see-through devices.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Instrument alignment is a common task in various surgical interventions using navigation. The goal of the task is to position and orient an instrument as it has been planned preoperatively. To this end, surgeons rely on patient-specific data visualized on screens alongside preplanned trajectories. The purpose of this manuscript is to investigate the effect of instrument visualization/non visualization on alignment tasks, and to compare it with virtual extensions approach which augments the realistic representation of the instrument with simple 3D objects. 18 volunteers performed six alignment tasks under each of the following conditions: no visualization on the instrument; realistic visualization of the instrument; realistic visualization extended with virtual elements (Virtual extensions). The first condition represents an egocentric-based alignment while the two other conditions additionally make use of exocentric depth estimation to perform the alignment. The device used was a see-through device (Microsoft HoloLens 2). The positions of the head and the instrument were acquired during the experiment. Additionally, the users were asked to fill NASA-TLX and SUS forms for each condition. The results show that instrument visualization is essential for a good alignment using see-through devices. Moreover, virtual extensions helped achieve the best performance compared to the other conditions with medians of 2 <italic>mm</italic> and 2° positional and angular error respectively. Furthermore, the virtual extensions decreased the average head velocity while similarly reducing the frustration levels. Therefore, making use of virtual extensions could facilitate alignment tasks in augmented and virtual reality (AR/VR) environments, specifically in AR navigated surgical procedures when using optical see-through devices.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Instrument alignment is a common task in various surgical interventions using navigation. The goal of the task is to position and orient an instrument as it has been planned preoperatively. To this end, surgeons rely on patient-specific data visualized on screens alongside preplanned trajectories. The purpose of this manuscript is to investigate the effect of instrument visualization/non visualization on alignment tasks, and to compare it with virtual extensions approach which augments the realistic representation of the instrument with simple 3D objects. 18 volunteers performed six alignment tasks under each of the following conditions: no visualization on the instrument; realistic visualization of the instrument; realistic visualization extended with virtual elements (Virtual extensions). The first condition represents an egocentric-based alignment while the two other conditions additionally make use of exocentric depth estimation to perform the alignment. The device used was a see-through device (Microsoft HoloLens 2). The positions of the head and the instrument were acquired during the experiment. Additionally, the users were asked to fill NASA-TLX and SUS forms for each condition. The results show that instrument visualization is essential for a good alignment using see-through devices. Moreover, virtual extensions helped achieve the best performance compared to the other conditions with medians of 2 mm and 2° positional and angular error respectively. Furthermore, the virtual extensions decreased the average head velocity while similarly reducing the frustration levels. Therefore, making use of virtual extensions could facilitate alignment tasks in augmented and virtual reality (AR/VR) environments, specifically in AR navigated surgical procedures when using optical see-through devices.",
"title": "Virtual extensions improve perception-based instrument alignment using optical see-through devices",
"normalizedTitle": "Virtual extensions improve perception-based instrument alignment using optical see-through devices",
"fno": "09523839",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Augmented Reality",
"Data Visualisation",
"Medical Computing",
"Navigation",
"Surgery",
"Perception Based Instrument Alignment",
"Virtual Extensions Approach",
"Realistic Visualization",
"Virtual Elements",
"Optical See Through Devices",
"3 D Objects",
"Egocentric Based Alignment",
"Exocentric Depth Estimation",
"Microsoft Holo Lens 2",
"SUS Forms",
"NASA TLX Forms",
"AR Navigated Surgical Procedures",
"Virtual Reality Environments",
"Augmented Reality Environments",
"Instruments",
"Task Analysis",
"Data Visualization",
"Surgery",
"Estimation",
"Three Dimensional Displays",
"Trajectory",
"User Study",
"Augmented Reality",
"Instrument Alignment",
"Alignment",
"Navigation System",
"Surgery"
],
"authors": [
{
"givenName": "Mohamed",
"surname": "Benmahdjoub",
"fullName": "Mohamed Benmahdjoub",
"affiliation": "Department of Radiology & Nuclear medicine and the Department of Oral and Maxillofacial Surgery, Erasmus MC, Biomedical Imaging Group Rotterdam, Rotterdam, The Netherlands",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Wiro J.",
"surname": "Niessen",
"fullName": "Wiro J. Niessen",
"affiliation": "Department of Radiology & Nuclear medicine, Erasmus MC, Biomedical Imaging Group Rotterdam, Rotterdam, The Netherlands",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Eppo B.",
"surname": "Wolvius",
"fullName": "Eppo B. Wolvius",
"affiliation": "Department of Oral and Maxillofacial Surgery, Erasmus MC, Rotterdam, The Netherlands",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Theo",
"surname": "van Walsum",
"fullName": "Theo van Walsum",
"affiliation": "Department of Radiology & Nuclear medicine, Erasmus MC, Biomedical Imaging Group Rotterdam, Rotterdam, The Netherlands",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "11",
"pubDate": "2021-11-01 00:00:00",
"pubType": "trans",
"pages": "4332-4341",
"year": "2021",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/3dui/2015/6886/0/07131769",
"title": "Crosscale: A 3D virtual musical instrument interface",
"doi": null,
"abstractUrl": "/proceedings-article/3dui/2015/07131769/12OmNBPc8zo",
"parentPublication": {
"id": "proceedings/3dui/2015/6886/0",
"title": "2015 IEEE Symposium on 3D User Interfaces (3DUI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aiccsa/2016/4320/0/07945729",
"title": "Handling occlusion in Augmented Reality surgical training based instrument tracking",
"doi": null,
"abstractUrl": "/proceedings-article/aiccsa/2016/07945729/12OmNvkGW33",
"parentPublication": {
"id": "proceedings/aiccsa/2016/4320/0",
"title": "2016 IEEE/ACS 13th International Conference of Computer Systems and Applications (AICCSA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/3dui/2016/0842/0/07460069",
"title": "A part-task haptic simulator for ophthalmic surgical training",
"doi": null,
"abstractUrl": "/proceedings-article/3dui/2016/07460069/12OmNwAKCQd",
"parentPublication": {
"id": "proceedings/3dui/2016/0842/0",
"title": "2016 IEEE Symposium on 3D User Interfaces (3DUI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vrw/2022/8402/0/840200a906",
"title": "Band Overdrive: A Multi-Instrument Virtual Reality Music Rhythm Game",
"doi": null,
"abstractUrl": "/proceedings-article/vrw/2022/840200a906/1CJcIGUC37O",
"parentPublication": {
"id": "proceedings/vrw/2022/8402/0",
"title": "2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibe/2022/8487/0/848700a164",
"title": "A Practical AR-based Surgical Navigation System Using Optical See-through Head Mounted Display",
"doi": null,
"abstractUrl": "/proceedings-article/bibe/2022/848700a164/1J6hB8fdg1W",
"parentPublication": {
"id": "proceedings/bibe/2022/8487/0",
"title": "2022 IEEE 22nd International Conference on Bioinformatics and Bioengineering (BIBE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmct/2022/7362/0/736200a010",
"title": "A Virtual Ethnic Musical Instrument Platform Based on Web App",
"doi": null,
"abstractUrl": "/proceedings-article/icmct/2022/736200a010/1Ml2hqurrva",
"parentPublication": {
"id": "proceedings/icmct/2022/7362/0",
"title": "2022 7th International Conference on Multimedia Communication Technologies (ICMCT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2019/1377/0/08798135",
"title": "Visualization Techniques for Precise Alignment in VR: A Comparative Study",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2019/08798135/1cJ0KovI6wo",
"parentPublication": {
"id": "proceedings/vr/2019/1377/0",
"title": "2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fie/2019/1746/0/09028525",
"title": "Development of the Value Alignment and Adaptation Strategies (VAAS) Instrument",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2019/09028525/1iffpGALx96",
"parentPublication": {
"id": "proceedings/fie/2019/1746/0",
"title": "2019 IEEE Frontiers in Education Conference (FIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar-adjunct/2020/7675/0/767500a045",
"title": "Evaluation of Different Visualization Techniques for Perception-Based Alignment in Medical AR",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2020/767500a045/1pBMfcK08fu",
"parentPublication": {
"id": "proceedings/ismar-adjunct/2020/7675/0",
"title": "2020 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccst/2021/4254/0/425400a330",
"title": "Method for Creation of Original Music by the VR Panorama Based Virtual Instrument",
"doi": null,
"abstractUrl": "/proceedings-article/iccst/2021/425400a330/1ziPn2wVnuE",
"parentPublication": {
"id": "proceedings/iccst/2021/4254/0",
"title": "2021 International Conference on Culture-oriented Science & Technology (ICCST)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09523893",
"articleId": "1wpqC4BIYla",
"__typename": "AdjacentArticleType"
},
"next": null,
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "12OmNzFdtc9",
"title": "Aug.",
"year": "2012",
"issueNum": "08",
"idPrefix": "tg",
"pubType": "journal",
"volume": "18",
"label": "Aug.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUxBa5xg",
"doi": "10.1109/TVCG.2012.141",
"abstract": null,
"abstracts": [
{
"abstractType": "Regular",
"content": "",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": null,
"title": "Guest Editor's Introduction: Special Section on the ACM SIGGRAPH/Eurographics Symposium on Computer Animation (SCA)",
"normalizedTitle": "Guest Editor's Introduction: Special Section on the ACM SIGGRAPH/Eurographics Symposium on Computer Animation (SCA)",
"fno": "ttg2012081189",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [],
"authors": [
{
"givenName": "Adam W.",
"surname": "Bargteil",
"fullName": "Adam W. Bargteil",
"affiliation": null,
"__typename": "ArticleAuthorType"
},
{
"givenName": "Michiel",
"surname": "van de Panne",
"fullName": "Michiel van de Panne",
"affiliation": null,
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": false,
"showRecommendedArticles": true,
"isOpenAccess": true,
"issueNum": "08",
"pubDate": "2012-08-01 00:00:00",
"pubType": "trans",
"pages": "1189-1190",
"year": "2012",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "mags/co/1987/04/01663536",
"title": "Eurographics'87",
"doi": null,
"abstractUrl": "/magazine/co/1987/04/01663536/13rRUB7a149",
"parentPublication": {
"id": "mags/co",
"title": "Computer",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2017/03/07835799",
"title": "Guest Editor's Introduction: Special Section on the ACM SIGGRAPH/Eurographics Symposium on Computer Animation (SCA)",
"doi": null,
"abstractUrl": "/journal/tg/2017/03/07835799/13rRUIIVlkm",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/1986/07/04056952",
"title": "ACM SIGGRAPH 86",
"doi": null,
"abstractUrl": "/magazine/cg/1986/07/04056952/13rRUwInvMt",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2014/01/ttg2014010002",
"title": "Guest Editor's Introduction: Special Section on the ACM SIGGRAPH/Eurographics Symposium on Computer Animation (SCA)",
"doi": null,
"abstractUrl": "/journal/tg/2014/01/ttg2014010002/13rRUwfZC0h",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2013/05/ttg2013050721",
"title": "Guest Editors' Introduction: Special Section on the ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games (I3D 2012)",
"doi": null,
"abstractUrl": "/journal/tg/2013/05/ttg2013050721/13rRUxBa5rV",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/1982/07/mcg1982070030",
"title": "Eurographics'82",
"doi": null,
"abstractUrl": "/magazine/cg/1982/07/mcg1982070030/13rRUxBa5zt",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/1989/05/mcg1989050014",
"title": "Siggraph",
"doi": null,
"abstractUrl": "/magazine/cg/1989/05/mcg1989050014/13rRUxC0SGn",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2017/10/08023920",
"title": "Introduction to the Special Section on the ACM/Eurographics Symposium on Computer Animation 2016",
"doi": null,
"abstractUrl": "/journal/tg/2017/10/08023920/13rRUxC0SWd",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2015/10/07230338",
"title": "Guest Editor's Introduction: Special Section on the ACM SIGGRAPH/Eurographics Symposium on Computer Animation (SCA)",
"doi": null,
"abstractUrl": "/journal/tg/2015/10/07230338/13rRUxOve9L",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2014/10/06881790",
"title": "Guest Editors' Introduction: Special Section on the ACM SIGGRAPH/Eurographics Symposium on Computer Animation (SCA)",
"doi": null,
"abstractUrl": "/journal/tg/2014/10/06881790/13rRUy0HYRq",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": null,
"next": {
"fno": "05963661",
"articleId": "13rRUxYIMUX",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "12OmNzFdtc9",
"title": "Aug.",
"year": "2012",
"issueNum": "08",
"idPrefix": "tg",
"pubType": "journal",
"volume": "18",
"label": "Aug.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUxYIMUX",
"doi": "10.1109/TVCG.2011.128",
"abstract": "We present a new approach for time-varying graph drawing that achieves both spatiotemporal coherence and multifocus+context visualization in a single framework. Our approach utilizes existing graph layout algorithms to produce the initial graph layout, and formulates the problem of generating coherent time-varying graph visualization with the focus+context capability as a specially tailored deformation optimization problem. We adopt the concept of the super graph to maintain spatiotemporal coherence and further balance the needs for aesthetic quality and dynamic stability when interacting with time-varying graphs through focus+context visualization. Our method is particularly useful for multifocus+context visualization of time-varying graphs where we can preserve the mental map by preventing nodes in the focus from undergoing abrupt changes in size and location in the time sequence. Experiments demonstrate that our method strikes a good balance between maintaining spatiotemporal coherence and accentuating visual foci, thus providing a more engaging viewing experience for the users.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We present a new approach for time-varying graph drawing that achieves both spatiotemporal coherence and multifocus+context visualization in a single framework. Our approach utilizes existing graph layout algorithms to produce the initial graph layout, and formulates the problem of generating coherent time-varying graph visualization with the focus+context capability as a specially tailored deformation optimization problem. We adopt the concept of the super graph to maintain spatiotemporal coherence and further balance the needs for aesthetic quality and dynamic stability when interacting with time-varying graphs through focus+context visualization. Our method is particularly useful for multifocus+context visualization of time-varying graphs where we can preserve the mental map by preventing nodes in the focus from undergoing abrupt changes in size and location in the time sequence. Experiments demonstrate that our method strikes a good balance between maintaining spatiotemporal coherence and accentuating visual foci, thus providing a more engaging viewing experience for the users.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We present a new approach for time-varying graph drawing that achieves both spatiotemporal coherence and multifocus+context visualization in a single framework. Our approach utilizes existing graph layout algorithms to produce the initial graph layout, and formulates the problem of generating coherent time-varying graph visualization with the focus+context capability as a specially tailored deformation optimization problem. We adopt the concept of the super graph to maintain spatiotemporal coherence and further balance the needs for aesthetic quality and dynamic stability when interacting with time-varying graphs through focus+context visualization. Our method is particularly useful for multifocus+context visualization of time-varying graphs where we can preserve the mental map by preventing nodes in the focus from undergoing abrupt changes in size and location in the time sequence. Experiments demonstrate that our method strikes a good balance between maintaining spatiotemporal coherence and accentuating visual foci, thus providing a more engaging viewing experience for the users.",
"title": "Coherent Time-Varying Graph Drawing with Multifocus+Context Interaction",
"normalizedTitle": "Coherent Time-Varying Graph Drawing with Multifocus+Context Interaction",
"fno": "05963661",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Optimisation",
"Graph Theory",
"Visual Foci",
"Coherent Time Varying Graph Drawing",
"Multifocus Context Interaction",
"Spatiotemporal Coherence",
"Multifocus Context Visualization",
"Graph Layout Algorithms",
"Coherent Time Varying Graph Visualization",
"Focus Context Capability",
"Deformation Optimization Problem",
"Aesthetic Quality",
"Dynamic Stability",
"Focus Context Visualization",
"Layout",
"Visualization",
"Context",
"Heuristic Algorithms",
"Coherence",
"Data Visualization",
"Spatiotemporal Phenomena",
"Focus Context Visualization",
"Graph Drawing",
"Time Varying Graphs",
"Spatiotemporal Coherence"
],
"authors": [
{
"givenName": null,
"surname": "Chaoli Wang",
"fullName": "Chaoli Wang",
"affiliation": "Dept. of Comput. Sci., Michigan Technol. Univ., Houghton, MI, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": null,
"surname": "Kun-Chuan Feng",
"fullName": "Kun-Chuan Feng",
"affiliation": "Dept. of Comput. Sci. & Inf. Eng, Nat. Cheng Kung Univ., Tainan, Taiwan",
"__typename": "ArticleAuthorType"
},
{
"givenName": null,
"surname": "Han-Wei Shen",
"fullName": "Han-Wei Shen",
"affiliation": "Dept. of Comput. Sci. & Eng., Ohio State Univ., Columbus, OH, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": null,
"surname": "Tong-Yee Lee",
"fullName": "Tong-Yee Lee",
"affiliation": "Dept. of Comput. Sci. & Inf. Eng, Nat. Cheng Kung Univ., Tainan, Taiwan",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "08",
"pubDate": "2012-08-01 00:00:00",
"pubType": "trans",
"pages": "1330-1342",
"year": "2012",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/icis/2005/2296/0/22960573",
"title": "Visualizing Hierarchical Information Using a New Focus+Context Method",
"doi": null,
"abstractUrl": "/proceedings-article/icis/2005/22960573/12OmNAJVcDe",
"parentPublication": {
"id": "proceedings/icis/2005/2296/0",
"title": "Proceedings. Fourth Annual ACIS International Conference on Computer and Information Science",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ieee-vis/2004/8788/0/87880147",
"title": "Visibility Culling for Time-Varying Volume Rendering Using Temporal Occlusion Coherence",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-vis/2004/87880147/12OmNAY79mS",
"parentPublication": {
"id": "proceedings/ieee-vis/2004/8788/0",
"title": "Visualization Conference, IEEE",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icvrv/2011/4602/0/4602a038",
"title": "Information Assisted Visualization of Large Scale Time Varying Scientific Data",
"doi": null,
"abstractUrl": "/proceedings-article/icvrv/2011/4602a038/12OmNBlFQX0",
"parentPublication": {
"id": "proceedings/icvrv/2011/4602/0",
"title": "2011 International Conference on Virtual Reality and Visualization",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sibgrapi/2013/5099/0/5099a107",
"title": "Multidimensional Projections to Explore Time-Varying Multivariate Volume Data",
"doi": null,
"abstractUrl": "/proceedings-article/sibgrapi/2013/5099a107/12OmNrkT7Pm",
"parentPublication": {
"id": "proceedings/sibgrapi/2013/5099/0",
"title": "2013 XXVI Conference on Graphics, Patterns and Images",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iita/2009/3859/2/3859b041",
"title": "Time Varying Coherence Spectrum Analysis of Multichannel Local Field Potentials and Neuronal Ensemble",
"doi": null,
"abstractUrl": "/proceedings-article/iita/2009/3859b041/12OmNwFicR7",
"parentPublication": {
"id": "proceedings/iita/2009/3859/2",
"title": "2009 Third International Symposium on Intelligent Information Technology Application",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ieee-vis/1999/5897/0/58970062",
"title": "A Fast Volume Rendering Algorithm for Time-Varying Fields Using a Time-Space Partitioning (TSP) Tree",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-vis/1999/58970062/12OmNxA3YU5",
"parentPublication": {
"id": "proceedings/ieee-vis/1999/5897/0",
"title": "Visualization Conference, IEEE",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ieee-vis/1998/9176/0/91760159",
"title": "Isosurface Extraction in Time-Varying Fields Using a Temporal Hierarchical Index Tree",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-vis/1998/91760159/12OmNxYL5dN",
"parentPublication": {
"id": "proceedings/ieee-vis/1998/9176/0",
"title": "Visualization Conference, IEEE",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ieee-infovis/2003/2055/0/20550008",
"title": "MoireGraphs: Radial Focus+Context Visualization and Interaction for Graphs with Visual Nodes",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-infovis/2003/20550008/12OmNxiKrV4",
"parentPublication": {
"id": "proceedings/ieee-infovis/2003/2055/0",
"title": "Information Visualization, IEEE Symposium on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2013/08/ttg2013081362",
"title": "Stack Zooming for Multifocus Interaction in Skewed-Aspect Visual Spaces",
"doi": null,
"abstractUrl": "/journal/tg/2013/08/ttg2013081362/13rRUx0xPi8",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2006/01/v0014",
"title": "Time-Varying Contour Topology",
"doi": null,
"abstractUrl": "/journal/tg/2006/01/v0014/13rRUzp02oc",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "ttg2012081189",
"articleId": "13rRUxBa5xg",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "05999664",
"articleId": "13rRUygT7sC",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "12OmNzFdtc9",
"title": "Aug.",
"year": "2012",
"issueNum": "08",
"idPrefix": "tg",
"pubType": "journal",
"volume": "18",
"label": "Aug.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUygT7sC",
"doi": "10.1109/TVCG.2011.142",
"abstract": "Networks are widely used to describe many natural and technological systems. Understanding how these evolve over time poses a challenge for existing visualization techniques originally developed for fixed network structures. We describe a method of incorporating the concept of aging into evolving networks, where nodes and edges store information related to the amount of local evolutionary change they have experienced. This property is used to generate visualizations that ensure stable substructures maintain relatively fixed spatial positions, allowing them to act as visual markers and providing context for evolutionary change elsewhere. By further supplementing these visualizations with color cues, the resultant animations enable a clearer portrayal of the underlying evolutionary process.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Networks are widely used to describe many natural and technological systems. Understanding how these evolve over time poses a challenge for existing visualization techniques originally developed for fixed network structures. We describe a method of incorporating the concept of aging into evolving networks, where nodes and edges store information related to the amount of local evolutionary change they have experienced. This property is used to generate visualizations that ensure stable substructures maintain relatively fixed spatial positions, allowing them to act as visual markers and providing context for evolutionary change elsewhere. By further supplementing these visualizations with color cues, the resultant animations enable a clearer portrayal of the underlying evolutionary process.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Networks are widely used to describe many natural and technological systems. Understanding how these evolve over time poses a challenge for existing visualization techniques originally developed for fixed network structures. We describe a method of incorporating the concept of aging into evolving networks, where nodes and edges store information related to the amount of local evolutionary change they have experienced. This property is used to generate visualizations that ensure stable substructures maintain relatively fixed spatial positions, allowing them to act as visual markers and providing context for evolutionary change elsewhere. By further supplementing these visualizations with color cues, the resultant animations enable a clearer portrayal of the underlying evolutionary process.",
"title": "Using Aging to Visually Uncover Evolutionary Processes on Networks",
"normalizedTitle": "Using Aging to Visually Uncover Evolutionary Processes on Networks",
"fno": "05999664",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Network Theory Graphs",
"Computer Animation",
"Data Visualisation",
"Evolutionary Computation",
"Animation",
"Network Aging",
"Evolutionary Process",
"Visualization Techniques",
"Network Structures",
"Visual Marker",
"Color Cues",
"Layout",
"Aging",
"Visualization",
"Data Visualization",
"Color",
"Animation",
"Stability Analysis",
"Graph Layout",
"Network Evolution",
"Information Visualization"
],
"authors": [
{
"givenName": "M.",
"surname": "di Bernardo",
"fullName": "M. di Bernardo",
"affiliation": "Dept. of Eng. Math., Univ. of Bristol, Bristol, UK",
"__typename": "ArticleAuthorType"
},
{
"givenName": "T. E.",
"surname": "Gorochowski",
"fullName": "T. E. Gorochowski",
"affiliation": "Dept. of Eng. Math., Univ. of Bristol, Bristol, UK",
"__typename": "ArticleAuthorType"
},
{
"givenName": "C. S.",
"surname": "Grierson",
"fullName": "C. S. Grierson",
"affiliation": "Sch. of Biol. Sci., Univ. of Bristol, Bristol, UK",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "08",
"pubDate": "2012-08-01 00:00:00",
"pubType": "trans",
"pages": "1343-1352",
"year": "2012",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/icn/2009/3552/0/3552a162",
"title": "Efficiency Analysis of Evolutionary Algorithm for Congestion Problem Using Computer Experimentation System",
"doi": null,
"abstractUrl": "/proceedings-article/icn/2009/3552a162/12OmNANkonw",
"parentPublication": {
"id": "proceedings/icn/2009/3552/0",
"title": "International Conference on Networking",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icnc/2009/3736/1/3736a378",
"title": "Wastewater DO Concentration Control through NH4 Prediction Based on Evolutionary Radial Basis Function Neural Network",
"doi": null,
"abstractUrl": "/proceedings-article/icnc/2009/3736a378/12OmNBO3Kkl",
"parentPublication": {
"id": "proceedings/icnc/2009/3736/4",
"title": "2009 Fifth International Conference on Natural Computation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bwcca/2011/4532/0/4532a515",
"title": "An Online Evolutionary Programming Method for Parameters of Wireless Networks",
"doi": null,
"abstractUrl": "/proceedings-article/bwcca/2011/4532a515/12OmNBscCTx",
"parentPublication": {
"id": "proceedings/bwcca/2011/4532/0",
"title": "2011 International Conference on Broadband and Wireless Computing, Communication and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/date/2005/2288/2/228821124",
"title": "Evolutionary Optimization in Code-Based Test Compression",
"doi": null,
"abstractUrl": "/proceedings-article/date/2005/228821124/12OmNxzMnVU",
"parentPublication": {
"id": "proceedings/date/2005/2288/2",
"title": "Design, Automation & Test in Europe Conference & Exhibition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icicta/2010/4077/1/4077a523",
"title": "A Hybrid Immune Evolutionary Algorithm for Global Optimization Search",
"doi": null,
"abstractUrl": "/proceedings-article/icicta/2010/4077a523/12OmNxzMo1f",
"parentPublication": {
"id": "proceedings/icicta/2010/4077/1",
"title": "Intelligent Computation Technology and Automation, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isorc/2009/3573/0/3573a012",
"title": "Delivering Sustainable Capability on Evolutionary Service-oriented Architecture",
"doi": null,
"abstractUrl": "/proceedings-article/isorc/2009/3573a012/12OmNyFU7b2",
"parentPublication": {
"id": "proceedings/isorc/2009/3573/0",
"title": "2009 IEEE International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/biovis/2011/0003/0/143150miller",
"title": "EVEVis: A multi-scale visualization system for dense evolutionary data",
"doi": null,
"abstractUrl": "/proceedings-article/biovis/2011/143150miller/12OmNzJbR1M",
"parentPublication": {
"id": "proceedings/biovis/2011/0003/0",
"title": "2011 IEEE Symposium on Biological Data Visualization (BioVis).",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/euromicro/2000/0780/1/07801156",
"title": "Application of Design Style in Evolutionary Multi-Level Networks Synthesis",
"doi": null,
"abstractUrl": "/proceedings-article/euromicro/2000/07801156/12OmNzsJ7jI",
"parentPublication": {
"id": "proceedings/euromicro/2000/0780/1",
"title": "EUROMICRO Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2001/08/i0786",
"title": "Hybrid Evolutionary Search Method Based on Clusters",
"doi": null,
"abstractUrl": "/journal/tp/2001/08/i0786/13rRUIJuxwd",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2019/2838/0/283800a292",
"title": "Data Visualization Scenarios for the Analysis of Computational Evolutionary Techniques",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2019/283800a292/1cMF9FQndQc",
"parentPublication": {
"id": "proceedings/iv/2019/2838/0",
"title": "2019 23rd International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "05963661",
"articleId": "13rRUxYIMUX",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "05999663",
"articleId": "13rRUyY28Ys",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "12OmNzFdtc9",
"title": "Aug.",
"year": "2012",
"issueNum": "08",
"idPrefix": "tg",
"pubType": "journal",
"volume": "18",
"label": "Aug.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUyY28Ys",
"doi": "10.1109/TVCG.2011.141",
"abstract": "A water drop behaves differently from a large water body because of its strong viscosity and surface tension under the small scale. Surface tension causes the motion of a water drop to be largely determined by its boundary surface. Meanwhile, viscosity makes the interior of a water drop less relevant to its motion, as the smooth velocity field can be well approximated by an interpolation of the velocity on the boundary. Consequently, we propose a fast deformable surface model to realistically animate water drops and their flowing behaviors on solid surfaces. Our system efficiently simulates water drop motions in a Lagrangian fashion, by reducing 3D fluid dynamics over the whole liquid volume to a deformable surface model. In each time step, the model uses an implicit mean curvature flow operator to produce surface tension effects, a contact angle operator to change droplet shapes on solid surfaces, and a set of mesh connectivity updates to handle topological changes and improve mesh quality over time. Our numerical experiments demonstrate a variety of physically plausible water drop phenomena at a real-time rate, including capillary waves when water drops collide, pinch-off of water jets, and droplets flowing over solid materials. The whole system performs orders-of-magnitude faster than existing simulation approaches that generate comparable water drop effects.",
"abstracts": [
{
"abstractType": "Regular",
"content": "A water drop behaves differently from a large water body because of its strong viscosity and surface tension under the small scale. Surface tension causes the motion of a water drop to be largely determined by its boundary surface. Meanwhile, viscosity makes the interior of a water drop less relevant to its motion, as the smooth velocity field can be well approximated by an interpolation of the velocity on the boundary. Consequently, we propose a fast deformable surface model to realistically animate water drops and their flowing behaviors on solid surfaces. Our system efficiently simulates water drop motions in a Lagrangian fashion, by reducing 3D fluid dynamics over the whole liquid volume to a deformable surface model. In each time step, the model uses an implicit mean curvature flow operator to produce surface tension effects, a contact angle operator to change droplet shapes on solid surfaces, and a set of mesh connectivity updates to handle topological changes and improve mesh quality over time. Our numerical experiments demonstrate a variety of physically plausible water drop phenomena at a real-time rate, including capillary waves when water drops collide, pinch-off of water jets, and droplets flowing over solid materials. The whole system performs orders-of-magnitude faster than existing simulation approaches that generate comparable water drop effects.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "A water drop behaves differently from a large water body because of its strong viscosity and surface tension under the small scale. Surface tension causes the motion of a water drop to be largely determined by its boundary surface. Meanwhile, viscosity makes the interior of a water drop less relevant to its motion, as the smooth velocity field can be well approximated by an interpolation of the velocity on the boundary. Consequently, we propose a fast deformable surface model to realistically animate water drops and their flowing behaviors on solid surfaces. Our system efficiently simulates water drop motions in a Lagrangian fashion, by reducing 3D fluid dynamics over the whole liquid volume to a deformable surface model. In each time step, the model uses an implicit mean curvature flow operator to produce surface tension effects, a contact angle operator to change droplet shapes on solid surfaces, and a set of mesh connectivity updates to handle topological changes and improve mesh quality over time. Our numerical experiments demonstrate a variety of physically plausible water drop phenomena at a real-time rate, including capillary waves when water drops collide, pinch-off of water jets, and droplets flowing over solid materials. The whole system performs orders-of-magnitude faster than existing simulation approaches that generate comparable water drop effects.",
"title": "A Deformable Surface Model for Real-Time Water Drop Animation",
"normalizedTitle": "A Deformable Surface Model for Real-Time Water Drop Animation",
"fno": "05999663",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Water",
"Approximation Theory",
"Capillary Waves",
"Computational Fluid Dynamics",
"Computer Animation",
"Contact Angle",
"Deformation",
"Drops",
"Flow Simulation",
"Interpolation",
"Jets",
"Mesh Generation",
"Surface Tension",
"Two Phase Flow",
"Viscosity",
"Flow Simulation",
"Deformable Surface Model",
"Real Time Water Drop Animation",
"Viscosity",
"Water Drop Motion",
"Boundary Surface",
"Interpolation",
"Approximation Theory",
"Lagrangian Theory",
"3 D Fluid Dynamics",
"Mean Curvature Flow Operator",
"Surface Tension Effect",
"Contact Angle Operator",
"Solid Surface",
"Mesh Connectivity",
"Mesh Quality Over Time",
"Water Drop Phenomena",
"Capillary Wave",
"Pinch Off",
"Water Jet",
"Droplets",
"Solid Material",
"Contact Angle",
"Solids",
"Surface Tension",
"Viscosity",
"Force",
"Deformable Models",
"Surface Waves",
"Numerical Models",
"Water Drop Simulation",
"Deformable Surface Model",
"Surface Tension",
"Mean Curvature Flow"
],
"authors": [
{
"givenName": null,
"surname": "Shuai Wang",
"fullName": "Shuai Wang",
"affiliation": "State Key Lab. of CAD&CG, Zhejiang Univ., Hangzhou, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": null,
"surname": "Huamin Wang",
"fullName": "Huamin Wang",
"affiliation": "Dept. of Comput. Sci. & Eng., Ohio State Univ., Columbus, OH, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": null,
"surname": "Yizhong Zhang",
"fullName": "Yizhong Zhang",
"affiliation": "State Key Lab. of CAD&CG, Zhejiang Univ., Hangzhou, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": null,
"surname": "Yiying Tong",
"fullName": "Yiying Tong",
"affiliation": "Dept. of Comput. Sci. & Eng., Michigan State Univ., East Lansing, MI, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": null,
"surname": "Kun Zhou",
"fullName": "Kun Zhou",
"affiliation": "State Key Lab. of CAD&CG, Zhejiang Univ., Hangzhou, China",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "08",
"pubDate": "2012-08-01 00:00:00",
"pubType": "trans",
"pages": "1281-1289",
"year": "2012",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/icvrv/2015/7673/0/7673a295",
"title": "SPH-based Fluid Simulation with a New Surface Tension Formulation",
"doi": null,
"abstractUrl": "/proceedings-article/icvrv/2015/7673a295/12OmNAS9zo4",
"parentPublication": {
"id": "proceedings/icvrv/2015/7673/0",
"title": "2015 International Conference on Virtual Reality and Visualization (ICVRV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cic/1989/2114/0/00130579",
"title": "A system for the measurement of drop volume of intravenous solutions",
"doi": null,
"abstractUrl": "/proceedings-article/cic/1989/00130579/12OmNBlofO3",
"parentPublication": {
"id": "proceedings/cic/1989/2114/0",
"title": "Proceedings Computers in Cardiology",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cad-graphics/2015/8020/0/07450421",
"title": "A New Surface Tension Formulation for SPH",
"doi": null,
"abstractUrl": "/proceedings-article/cad-graphics/2015/07450421/12OmNButq4h",
"parentPublication": {
"id": "proceedings/cad-graphics/2015/8020/0",
"title": "2015 14th International Conference on Computer-Aided Design and Computer Graphics (CAD/Graphics)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvmp/2011/4621/0/4621a109",
"title": "Realtime Video Based Water Surface Approximation",
"doi": null,
"abstractUrl": "/proceedings-article/cvmp/2011/4621a109/12OmNscxj23",
"parentPublication": {
"id": "proceedings/cvmp/2011/4621/0",
"title": "2011 Conference for Visual Media Production",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdl/2002/7350/0/01022734",
"title": "Instability of electrically stressed water droplets in oil",
"doi": null,
"abstractUrl": "/proceedings-article/icdl/2002/01022734/12OmNweBUD0",
"parentPublication": {
"id": "proceedings/icdl/2002/7350/0",
"title": "Proceedings of 14th International Conference on Dielectric Liquids",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccis/2011/4501/0/4501a549",
"title": "The Simulation of Non-heating Pipelines' Temperature Drop under Stopping Mixing Water Condition",
"doi": null,
"abstractUrl": "/proceedings-article/iccis/2011/4501a549/12OmNwudQN5",
"parentPublication": {
"id": "proceedings/iccis/2011/4501/0",
"title": "2011 International Conference on Computational and Information Sciences",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isdea/2013/4893/0/06456676",
"title": "Characteristics and Evaluation for Nitrogen Pollution in Water and Surface Sediments of Xixi Wetland",
"doi": null,
"abstractUrl": "/proceedings-article/isdea/2013/06456676/12OmNyL0TFJ",
"parentPublication": {
"id": "proceedings/isdea/2013/4893/0",
"title": "2013 Third International Conference on Intelligent System Design and Engineering Applications (ISDEA 2013)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cs/2006/05/c5081",
"title": "Water Wave Animation on Mesh Surfaces",
"doi": null,
"abstractUrl": "/magazine/cs/2006/05/c5081/13rRUwkfAUs",
"parentPublication": {
"id": "mags/cs",
"title": "Computing in Science & Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ithings-greencom-cpscom-smartdata/2019/2980/0/298000a675",
"title": "An Improved Otsu Method Based on Uniformity Measurement for Segmentation of Water Surface Images",
"doi": null,
"abstractUrl": "/proceedings-article/ithings-greencom-cpscom-smartdata/2019/298000a675/1ehBKbmDmg0",
"parentPublication": {
"id": "proceedings/ithings-greencom-cpscom-smartdata/2019/2980/0",
"title": "2019 International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2022/12/09583771",
"title": "Surface Normals and Shape From Water",
"doi": null,
"abstractUrl": "/journal/tp/2022/12/09583771/1xSHN8Dq0HS",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "05999664",
"articleId": "13rRUygT7sC",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "06200365",
"articleId": "13rRUyp7tWV",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "12OmNzFdtc9",
"title": "Aug.",
"year": "2012",
"issueNum": "08",
"idPrefix": "tg",
"pubType": "journal",
"volume": "18",
"label": "Aug.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUyp7tWV",
"doi": "10.1109/TVCG.2011.151",
"abstract": "Treating the interactions of soft tissue with rigid user-guided tools is a difficult problem. This is particularly true if the soft tissue has a slender shape, i.e., resembling a thin shell, and if the underlying numerical time-integration scheme employs large time steps. In this case, large mutual displacements of both the tool and the soft tissue occur frequently, resulting in deep interpenetrations or breakthroughs. As a consequence, the computation of spatially and temporally coherent contact spaces turns out to be very challenging. In this paper, an approach is proposed that is tailored to these kinds of interactions. To solve this problem, a novel spatially reduced representation of the soft tissue geometry is employed where the dominant dimensions of the object are approximated by a 2D triangle surface, while the third dimension is given in terms of nodal radii. To construct a feasible, nonpenetrating configuration, a novel manifold projection scheme is presented where the colliding triangles are rasterized into a distance field in order to robustly estimate the contact spaces, even for large intersections. The method produces physically plausible results, albeit it is purely geometric, and the material parameters are neglected at the collision response stage. Various examples, including an interactive prototype arthroscopy simulator, underline the wide applicability of the approach.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Treating the interactions of soft tissue with rigid user-guided tools is a difficult problem. This is particularly true if the soft tissue has a slender shape, i.e., resembling a thin shell, and if the underlying numerical time-integration scheme employs large time steps. In this case, large mutual displacements of both the tool and the soft tissue occur frequently, resulting in deep interpenetrations or breakthroughs. As a consequence, the computation of spatially and temporally coherent contact spaces turns out to be very challenging. In this paper, an approach is proposed that is tailored to these kinds of interactions. To solve this problem, a novel spatially reduced representation of the soft tissue geometry is employed where the dominant dimensions of the object are approximated by a 2D triangle surface, while the third dimension is given in terms of nodal radii. To construct a feasible, nonpenetrating configuration, a novel manifold projection scheme is presented where the colliding triangles are rasterized into a distance field in order to robustly estimate the contact spaces, even for large intersections. The method produces physically plausible results, albeit it is purely geometric, and the material parameters are neglected at the collision response stage. Various examples, including an interactive prototype arthroscopy simulator, underline the wide applicability of the approach.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Treating the interactions of soft tissue with rigid user-guided tools is a difficult problem. This is particularly true if the soft tissue has a slender shape, i.e., resembling a thin shell, and if the underlying numerical time-integration scheme employs large time steps. In this case, large mutual displacements of both the tool and the soft tissue occur frequently, resulting in deep interpenetrations or breakthroughs. As a consequence, the computation of spatially and temporally coherent contact spaces turns out to be very challenging. In this paper, an approach is proposed that is tailored to these kinds of interactions. To solve this problem, a novel spatially reduced representation of the soft tissue geometry is employed where the dominant dimensions of the object are approximated by a 2D triangle surface, while the third dimension is given in terms of nodal radii. To construct a feasible, nonpenetrating configuration, a novel manifold projection scheme is presented where the colliding triangles are rasterized into a distance field in order to robustly estimate the contact spaces, even for large intersections. The method produces physically plausible results, albeit it is purely geometric, and the material parameters are neglected at the collision response stage. Various examples, including an interactive prototype arthroscopy simulator, underline the wide applicability of the approach.",
"title": "Robust Interactive Collision Handling between Tools and Thin Volumetric Objects",
"normalizedTitle": "Robust Interactive Collision Handling between Tools and Thin Volumetric Objects",
"fno": "06200365",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Surgery",
"Biological Tissues",
"Computational Geometry",
"Interactive Systems",
"Medical Computing",
"Interactive Prototype Arthroscopy Simulator",
"Robust Interactive Collision Handling",
"Thin Volumetric Objects",
"Rigid User Guided Tools",
"Numerical Time Integration Scheme",
"Mutual Displacements",
"Temporally Coherent Contact Spaces",
"Spatially Coherent Contact Spaces",
"Spatially Reduced Representation",
"Soft Tissue Geometry",
"2 D Triangle Surface",
"Manifold Projection Scheme",
"Colliding Triangles",
"Material Parameters",
"Collision Response Stage",
"Geometry",
"Computational Modeling",
"Deformable Models",
"Shape",
"Biological Tissues",
"Manifolds",
"Robustness",
"Gauss Seidel",
"Physically Based Simulation",
"Collision Handling",
"Soft Tissue",
"Distance Fields"
],
"authors": [
{
"givenName": "J.",
"surname": "Spillmann",
"fullName": "J. Spillmann",
"affiliation": "Comput. Vision Lab., ETH Zurich, Zurich, Switzerland",
"__typename": "ArticleAuthorType"
},
{
"givenName": "M.",
"surname": "Harders",
"fullName": "M. Harders",
"affiliation": "Comput. Vision Lab., ETH Zurich, Zurich, Switzerland",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "08",
"pubDate": "2012-08-01 00:00:00",
"pubType": "trans",
"pages": "1241-1254",
"year": "2012",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/mines/2011/4559/0/4559a060",
"title": "Simulation of Soft Tissue Deformation in Virtual Surgery Based on Physics Engine",
"doi": null,
"abstractUrl": "/proceedings-article/mines/2011/4559a060/12OmNBuL1jc",
"parentPublication": {
"id": "proceedings/mines/2011/4559/0",
"title": "Multimedia Information Networking and Security, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/haptics/2010/6821/0/05444609",
"title": "Towards physics-based interactive simulation of electrocautery procedures using PhysX",
"doi": null,
"abstractUrl": "/proceedings-article/haptics/2010/05444609/12OmNBzRNsx",
"parentPublication": {
"id": "proceedings/haptics/2010/6821/0",
"title": "2010 IEEE Haptics Symposium (Formerly known as Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/csie/2009/3507/2/3507b186",
"title": "A Novel Method for Boundary Condition Computation in Soft Tissue Deformation",
"doi": null,
"abstractUrl": "/proceedings-article/csie/2009/3507b186/12OmNrYlmOp",
"parentPublication": {
"id": "proceedings/csie/2009/3507/2",
"title": "Computer Science and Information Engineering, World Congress on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/trustcom/2011/2135/0/06121000",
"title": "Nose Surgery Simulation Based on Volumetric Laplacian Deformation",
"doi": null,
"abstractUrl": "/proceedings-article/trustcom/2011/06121000/12OmNvSbBqY",
"parentPublication": {
"id": "proceedings/trustcom/2011/2135/0",
"title": "2011IEEE 10th International Conference on Trust, Security and Privacy in Computing and Communications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2013/1309/0/06732698",
"title": "Investigation on the feasibility of selecting soft tissue elasticity as the objective evaluating indicator of the neck type of cervical spondylosis",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2013/06732698/12OmNxGAKR5",
"parentPublication": {
"id": "proceedings/bibm/2013/1309/0",
"title": "2013 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/haptics/2010/6821/0/05444685",
"title": "Human vs. robotic tactile sensing: Detecting lumps in soft tissue",
"doi": null,
"abstractUrl": "/proceedings-article/haptics/2010/05444685/12OmNxTVU0U",
"parentPublication": {
"id": "proceedings/haptics/2010/6821/0",
"title": "2010 IEEE Haptics Symposium (Formerly known as Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iciev-iscmht/2017/1023/0/08338517",
"title": "Development of a capacitive force sensor for artificial joint",
"doi": null,
"abstractUrl": "/proceedings-article/iciev-iscmht/2017/08338517/12OmNzA6GHa",
"parentPublication": {
"id": "proceedings/iciev-iscmht/2017/1023/0",
"title": "2017 6th International Conference on Informatics, Electronics and Vision & 2017 7th International Symposium in Computational Medical and Health Technology (ICIEV-ISCMHT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2014/11/06872553",
"title": "Generating Facial Expressions Using an Anatomically Accurate Biomechanical Model",
"doi": null,
"abstractUrl": "/journal/tg/2014/11/06872553/13rRUwI5Uga",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iceitsa/2021/1300/0/130000a166",
"title": "Prediction Model of Target Movement in Soft Tissue Under Needle Puncture",
"doi": null,
"abstractUrl": "/proceedings-article/iceitsa/2021/130000a166/1B2HpcUZC6s",
"parentPublication": {
"id": "proceedings/iceitsa/2021/1300/0",
"title": "2021 International Conference on Electronic Information Technology and Smart Agriculture (ICEITSA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2021/4509/0/450900b471",
"title": "ContactOpt: Optimizing Contact to Improve Grasps",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2021/450900b471/1yeMkzSzpIc",
"parentPublication": {
"id": "proceedings/cvpr/2021/4509/0",
"title": "2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "05999663",
"articleId": "13rRUyY28Ys",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "06025348",
"articleId": "13rRUyY28Yt",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "12OmNzFdtc9",
"title": "Aug.",
"year": "2012",
"issueNum": "08",
"idPrefix": "tg",
"pubType": "journal",
"volume": "18",
"label": "Aug.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUyY28Yt",
"doi": "10.1109/TVCG.2011.155",
"abstract": "Effective 3D streamline placement and visualization play an essential role in many science and engineering disciplines. The main challenge for effective streamline visualization lies in seed placement, i.e., where to drop seeds and how many seeds should be placed. Seeding too many or too few streamlines may not reveal flow features and patterns either because it easily leads to visual clutter in rendering or it conveys little information about the flow field. Not only does the number of streamlines placed matter, their spatial relationships also play a key role in understanding the flow field. Therefore, effective flow visualization requires the streamlines to be placed in the right place and in the right amount. This paper introduces hierarchical streamline bundles, a novel approach to simplifying and visualizing 3D flow fields defined on regular grids. By placing seeds and generating streamlines according to flow saliency, we produce a set of streamlines that captures important flow features near critical points without enforcing the dense seeding condition. We group spatially neighboring and geometrically similar streamlines to construct a hierarchy from which we extract streamline bundles at different levels of detail. Streamline bundles highlight multiscale flow features and patterns through clustered yet not cluttered display. This selective visualization strategy effectively reduces visual clutter while accentuating visual foci, and therefore is able to convey the desired insight into the flow data.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Effective 3D streamline placement and visualization play an essential role in many science and engineering disciplines. The main challenge for effective streamline visualization lies in seed placement, i.e., where to drop seeds and how many seeds should be placed. Seeding too many or too few streamlines may not reveal flow features and patterns either because it easily leads to visual clutter in rendering or it conveys little information about the flow field. Not only does the number of streamlines placed matter, their spatial relationships also play a key role in understanding the flow field. Therefore, effective flow visualization requires the streamlines to be placed in the right place and in the right amount. This paper introduces hierarchical streamline bundles, a novel approach to simplifying and visualizing 3D flow fields defined on regular grids. By placing seeds and generating streamlines according to flow saliency, we produce a set of streamlines that captures important flow features near critical points without enforcing the dense seeding condition. We group spatially neighboring and geometrically similar streamlines to construct a hierarchy from which we extract streamline bundles at different levels of detail. Streamline bundles highlight multiscale flow features and patterns through clustered yet not cluttered display. This selective visualization strategy effectively reduces visual clutter while accentuating visual foci, and therefore is able to convey the desired insight into the flow data.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Effective 3D streamline placement and visualization play an essential role in many science and engineering disciplines. The main challenge for effective streamline visualization lies in seed placement, i.e., where to drop seeds and how many seeds should be placed. Seeding too many or too few streamlines may not reveal flow features and patterns either because it easily leads to visual clutter in rendering or it conveys little information about the flow field. Not only does the number of streamlines placed matter, their spatial relationships also play a key role in understanding the flow field. Therefore, effective flow visualization requires the streamlines to be placed in the right place and in the right amount. This paper introduces hierarchical streamline bundles, a novel approach to simplifying and visualizing 3D flow fields defined on regular grids. By placing seeds and generating streamlines according to flow saliency, we produce a set of streamlines that captures important flow features near critical points without enforcing the dense seeding condition. We group spatially neighboring and geometrically similar streamlines to construct a hierarchy from which we extract streamline bundles at different levels of detail. Streamline bundles highlight multiscale flow features and patterns through clustered yet not cluttered display. This selective visualization strategy effectively reduces visual clutter while accentuating visual foci, and therefore is able to convey the desired insight into the flow data.",
"title": "Hierarchical Streamline Bundles",
"normalizedTitle": "Hierarchical Streamline Bundles",
"fno": "06025348",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Rendering Computer Graphics",
"Critical Points",
"Flow Visualisation",
"Pattern Clustering",
"Pattern Formation",
"Critical Points",
"Hierarchical Streamline Bundles",
"3 D Streamline Placement",
"3 D Streamline Visualization",
"Seed Placement",
"Rendering",
"Spatial Relationships",
"3 D Flow Field Visualization",
"Spatially Neighboring Streamlines",
"Geometrically Similar Streamlines",
"Streamline Bundle Extraction",
"Multiscale Flow Features",
"Multiscale Flow Patterns",
"Visual Clutter Reduction",
"Visual Foci Accentuation",
"Flow Data",
"Flow Saliency",
"Streamline Seeding",
"Three Dimensional Displays",
"Streaming Media",
"Feature Extraction",
"Data Visualization",
"Clustering Algorithms",
"Visualization",
"Diffusion Tensor Imaging",
"Flow Visualization",
"Streamline Bundles",
"Flow Saliency",
"Seed Placement",
"Hierarchical Clustering",
"Level Of Detail"
],
"authors": [
{
"givenName": null,
"surname": "Ching-Kuang Shene",
"fullName": "Ching-Kuang Shene",
"affiliation": "Dept. of Comput. Sci., Michigan Technol. Univ., Townsend, MA, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": null,
"surname": "Chaoli Wang",
"fullName": "Chaoli Wang",
"affiliation": "Dept. of Comput. Sci., Michigan Technol. Univ., Townsend, MA, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": null,
"surname": "Hongfeng Yu",
"fullName": "Hongfeng Yu",
"affiliation": "Combustion Res. Facility, Sandia Nat. Labs., Livermore, CA, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "J. H.",
"surname": "Chen",
"fullName": "J. H. Chen",
"affiliation": "Combustion Res. Facility, Sandia Nat. Labs., Livermore, CA, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "08",
"pubDate": "2012-08-01 00:00:00",
"pubType": "trans",
"pages": "1353-1367",
"year": "2012",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/ieee-vis/1998/9176/0/91760135",
"title": "Image-Guided Streamline Placement on Curvilinear Grid Surfaces",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-vis/1998/91760135/12OmNCbU2XH",
"parentPublication": {
"id": "proceedings/ieee-vis/1998/9176/0",
"title": "Visualization Conference, IEEE",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cis/2010/4297/0/4297a238",
"title": "A Streamline Placement Method Highlighting Flow Field Topology",
"doi": null,
"abstractUrl": "/proceedings-article/cis/2010/4297a238/12OmNvF83qx",
"parentPublication": {
"id": "proceedings/cis/2010/4297/0",
"title": "2010 International Conference on Computational Intelligence and Security",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cis/2011/4584/0/4584b224",
"title": "Streamline-based Visualization of 3D Explosion Fields",
"doi": null,
"abstractUrl": "/proceedings-article/cis/2011/4584b224/12OmNwtEEJX",
"parentPublication": {
"id": "proceedings/cis/2011/4584/0",
"title": "2011 Seventh International Conference on Computational Intelligence and Security",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ieee-vis/2000/6478/0/64780027",
"title": "A Flow-guided Streamline Seeding Strategy",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-vis/2000/64780027/12OmNxI0Kvw",
"parentPublication": {
"id": "proceedings/ieee-vis/2000/6478/0",
"title": "Visualization Conference, IEEE",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cis/2011/4584/0/4584b174",
"title": "Multiresolution Streamline Placement for 2D Flow Fields",
"doi": null,
"abstractUrl": "/proceedings-article/cis/2011/4584b174/12OmNz6iOml",
"parentPublication": {
"id": "proceedings/cis/2011/4584/0",
"title": "2011 Seventh International Conference on Computational Intelligence and Security",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2013/08/ttg2013081342",
"title": "Similarity Measures for Enhancing Interactive Streamline Seeding",
"doi": null,
"abstractUrl": "/journal/tg/2013/08/ttg2013081342/13rRUwInvB3",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2007/03/v0630",
"title": "Image-Based Streamline Generation and Rendering",
"doi": null,
"abstractUrl": "/journal/tg/2007/03/v0630/13rRUwdIOUC",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2006/06/v1601",
"title": "Streamline Predicates",
"doi": null,
"abstractUrl": "/journal/tg/2006/06/v1601/13rRUwfZC06",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2010/05/ttg2010050791",
"title": "Topology-Aware Evenly Spaced Streamline Placement",
"doi": null,
"abstractUrl": "/journal/tg/2010/05/ttg2010050791/13rRUwvT9gp",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2013/07/ttg2013071185",
"title": "Parallel Streamline Placement for 2D Flow Fields",
"doi": null,
"abstractUrl": "/journal/tg/2013/07/ttg2013071185/13rRUyfbwqG",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "06200365",
"articleId": "13rRUyp7tWV",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "05989803",
"articleId": "13rRUxNW1TR",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "12OmNzFdtc9",
"title": "Aug.",
"year": "2012",
"issueNum": "08",
"idPrefix": "tg",
"pubType": "journal",
"volume": "18",
"label": "Aug.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUxNW1TR",
"doi": "10.1109/TVCG.2011.140",
"abstract": "This paper presents a very easy-to-use interactive tool, which we call dot scissor, for mesh segmentation. The user's effort is reduced to placing only a single click where a cut is desired. Such a simple interface is made possible by a directional search strategy supported by a concavity-aware harmonic field and a robust voting scheme that selects the best isoline as the cut. With a concavity-aware weighting scheme, the harmonic fields gather dense isolines along concave regions which are natural boundaries of semantic components. The voting scheme relies on an isoline-face scoring mechanism that considers both shape geometry and user intent. We show by extensive experiments and quantitative analysis that our tool advances the state-of-the-art segmentation methods in both simplicity of use and segmentation quality.",
"abstracts": [
{
"abstractType": "Regular",
"content": "This paper presents a very easy-to-use interactive tool, which we call dot scissor, for mesh segmentation. The user's effort is reduced to placing only a single click where a cut is desired. Such a simple interface is made possible by a directional search strategy supported by a concavity-aware harmonic field and a robust voting scheme that selects the best isoline as the cut. With a concavity-aware weighting scheme, the harmonic fields gather dense isolines along concave regions which are natural boundaries of semantic components. The voting scheme relies on an isoline-face scoring mechanism that considers both shape geometry and user intent. We show by extensive experiments and quantitative analysis that our tool advances the state-of-the-art segmentation methods in both simplicity of use and segmentation quality.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "This paper presents a very easy-to-use interactive tool, which we call dot scissor, for mesh segmentation. The user's effort is reduced to placing only a single click where a cut is desired. Such a simple interface is made possible by a directional search strategy supported by a concavity-aware harmonic field and a robust voting scheme that selects the best isoline as the cut. With a concavity-aware weighting scheme, the harmonic fields gather dense isolines along concave regions which are natural boundaries of semantic components. The voting scheme relies on an isoline-face scoring mechanism that considers both shape geometry and user intent. We show by extensive experiments and quantitative analysis that our tool advances the state-of-the-art segmentation methods in both simplicity of use and segmentation quality.",
"title": "Dot Scissor: A Single-Click Interface for Mesh Segmentation",
"normalizedTitle": "Dot Scissor: A Single-Click Interface for Mesh Segmentation",
"fno": "05989803",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"User Interfaces",
"Computer Graphics",
"Interactive Systems",
"Mesh Generation",
"Search Problems",
"Segmentation Quality",
"Dot Scissor",
"Single Click Interface",
"Mesh Segmentation",
"Easy To Use Interactive Tool",
"Directional Search Strategy",
"Concavity Aware Harmonic Field",
"Robust Voting Scheme",
"Concavity Aware Weighting Scheme",
"Natural Boundaries",
"Semantic Components",
"Isoline Face Scoring Mechanism",
"Shape Geometry",
"Quantitative Analysis",
"State Of The Art Segmentation Methods",
"Harmonic Analysis",
"Shape",
"Brushes",
"Robustness",
"Geometry",
"Humans",
"Gold",
"Voting",
"Interactive Mesh Segmentation",
"Dot Scissor",
"Concavity Aware",
"Harmonic Fields"
],
"authors": [
{
"givenName": null,
"surname": "Chiew-Lan Tai",
"fullName": "Chiew-Lan Tai",
"affiliation": "Dept. of Comput. Sci. & Eng., Hong Kong Univ. of Sci. & Technol., Kowloon, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": null,
"surname": "Youyi Zheng",
"fullName": "Youyi Zheng",
"affiliation": "Dept. of Comput. Sci. & Eng., Hong Kong Univ. of Sci. & Technol., Kowloon, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "O. K-C",
"surname": "Au",
"fullName": "O. K-C Au",
"affiliation": "Sch. of Creative Media, City Univ. of Hong Kong, Kowloon, China",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "08",
"pubDate": "2012-08-01 00:00:00",
"pubType": "trans",
"pages": "1304-1312",
"year": "2012",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/cmsp/2011/4356/1/4356a184",
"title": "Consistent Mesh Segmentation Using Protrusion Function and Graph Cut",
"doi": null,
"abstractUrl": "/proceedings-article/cmsp/2011/4356a184/12OmNBW0vCO",
"parentPublication": {
"id": "proceedings/cmsp/2011/4356/1",
"title": "Multimedia and Signal Processing, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sibgrapi/2011/4548/0/4548a266",
"title": "Spectral Segmentation Using Cartoon-Texture Decomposition and Inner Product-Based Metric",
"doi": null,
"abstractUrl": "/proceedings-article/sibgrapi/2011/4548a266/12OmNwDSdfY",
"parentPublication": {
"id": "proceedings/sibgrapi/2011/4548/0",
"title": "2011 24th SIBGRAPI Conference on Graphics, Patterns and Images",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdh/2012/4899/0/4899a449",
"title": "3D Mesh Segmentation Based on Multiclass Spectral Graph Partition",
"doi": null,
"abstractUrl": "/proceedings-article/icdh/2012/4899a449/12OmNx5piPR",
"parentPublication": {
"id": "proceedings/icdh/2012/4899/0",
"title": "4th International Conference on Digital Home (ICDH)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/2015/06/mcg2015060051",
"title": "Angle-Preserving Quadrilateral Mesh Parameterization",
"doi": null,
"abstractUrl": "/magazine/cg/2015/06/mcg2015060051/13rRUxBa5pf",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2012/07/ttg2012071125",
"title": "Mesh Segmentation with Concavity-Aware Fields",
"doi": null,
"abstractUrl": "/journal/tg/2012/07/ttg2012071125/13rRUxBrGgV",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2020/7168/0/716800d842",
"title": "Instance Segmentation of Biological Images Using Harmonic Embeddings",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2020/716800d842/1m3nMWggsZa",
"parentPublication": {
"id": "proceedings/cvpr/2020/7168/0",
"title": "2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "06025348",
"articleId": "13rRUyY28Yt",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "06007132",
"articleId": "13rRUygT7y9",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "12OmNzFdtc9",
"title": "Aug.",
"year": "2012",
"issueNum": "08",
"idPrefix": "tg",
"pubType": "journal",
"volume": "18",
"label": "Aug.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUygT7y9",
"doi": "10.1109/TVCG.2011.144",
"abstract": "Security Visualization is a very young term. It expresses the idea that common visualization techniques have been designed for use cases that are not supportive of security-related data, demanding novel techniques fine tuned for the purpose of thorough analysis. Significant amount of work has been published in this area, but little work has been done to study this emerging visualization discipline. We offer a comprehensive review of network security visualization and provide a taxonomy in the form of five use-case classes encompassing nearly all recent works in this area. We outline the incorporated visualization techniques and data sources and provide an informative table to display our findings. From the analysis of these systems, we examine issues and concerns regarding network security visualization and provide guidelines and directions for future researchers and visual system developers.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Security Visualization is a very young term. It expresses the idea that common visualization techniques have been designed for use cases that are not supportive of security-related data, demanding novel techniques fine tuned for the purpose of thorough analysis. Significant amount of work has been published in this area, but little work has been done to study this emerging visualization discipline. We offer a comprehensive review of network security visualization and provide a taxonomy in the form of five use-case classes encompassing nearly all recent works in this area. We outline the incorporated visualization techniques and data sources and provide an informative table to display our findings. From the analysis of these systems, we examine issues and concerns regarding network security visualization and provide guidelines and directions for future researchers and visual system developers.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Security Visualization is a very young term. It expresses the idea that common visualization techniques have been designed for use cases that are not supportive of security-related data, demanding novel techniques fine tuned for the purpose of thorough analysis. Significant amount of work has been published in this area, but little work has been done to study this emerging visualization discipline. We offer a comprehensive review of network security visualization and provide a taxonomy in the form of five use-case classes encompassing nearly all recent works in this area. We outline the incorporated visualization techniques and data sources and provide an informative table to display our findings. From the analysis of these systems, we examine issues and concerns regarding network security visualization and provide guidelines and directions for future researchers and visual system developers.",
"title": "A Survey of Visualization Systems for Network Security",
"normalizedTitle": "A Survey of Visualization Systems for Network Security",
"fno": "06007132",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Data Visualisation",
"Computer Network Security",
"Information Visualization",
"Network Security Visualization System",
"Security Related Data",
"Taxonomy",
"Use Case Classes",
"Data Sources",
"Informative Table",
"Data Visualization",
"Security",
"Servers",
"Visualization",
"Monitoring",
"Feature Extraction",
"IP Networks",
"Visualization Techniques",
"Information Visualization",
"Network Security Visualization"
],
"authors": [
{
"givenName": "A.",
"surname": "Shiravi",
"fullName": "A. Shiravi",
"affiliation": "Inf. Security Centre of Excellence, Univ. of New Brunswick, Fredericton, NB, Canada",
"__typename": "ArticleAuthorType"
},
{
"givenName": "H.",
"surname": "Shiravi",
"fullName": "H. Shiravi",
"affiliation": "Inf. Security Centre of Excellence, Univ. of New Brunswick, Fredericton, NB, Canada",
"__typename": "ArticleAuthorType"
},
{
"givenName": "A. A.",
"surname": "Ghorbani",
"fullName": "A. A. Ghorbani",
"affiliation": "Inf. Security Centre of Excellence, Univ. of New Brunswick, Fredericton, NB, Canada",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "08",
"pubDate": "2012-08-01 00:00:00",
"pubType": "trans",
"pages": "1313-1329",
"year": "2012",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/ncm/2008/3322/1/3322a129",
"title": "A Survey on Visualization for Wireless Security",
"doi": null,
"abstractUrl": "/proceedings-article/ncm/2008/3322a129/12OmNB1eJxF",
"parentPublication": {
"id": "proceedings/ncm/2008/3322/1",
"title": "Networked Computing and Advanced Information Management, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/mines/2011/4559/0/4559a411",
"title": "Network Security Situation Awareness Method Based on Visualization",
"doi": null,
"abstractUrl": "/proceedings-article/mines/2011/4559a411/12OmNBOCWt1",
"parentPublication": {
"id": "proceedings/mines/2011/4559/0",
"title": "Multimedia Information Networking and Security, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vizsec/2015/7599/0/07312766",
"title": "Ensemble visualization for cyber situation awareness of network security data",
"doi": null,
"abstractUrl": "/proceedings-article/vizsec/2015/07312766/12OmNC4eSCa",
"parentPublication": {
"id": "proceedings/vizsec/2015/7599/0",
"title": "2015 IEEE Symposium on Visualization for Cyber Security (VizSec)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cicsyn/2010/4158/0/4158a227",
"title": "Expert-Aware Approach: A New Approach to Improve Network Security Visualization Tool",
"doi": null,
"abstractUrl": "/proceedings-article/cicsyn/2010/4158a227/12OmNCxbXAF",
"parentPublication": {
"id": "proceedings/cicsyn/2010/4158/0",
"title": "Computational Intelligence, Communication Systems and Networks, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pdp/2013/4939/0/4939a519",
"title": "Analytical Visualization Techniques for Security Information and Event Management",
"doi": null,
"abstractUrl": "/proceedings-article/pdp/2013/4939a519/12OmNrNh0ss",
"parentPublication": {
"id": "proceedings/pdp/2013/4939/0",
"title": "2013 21st Euromicro International Conference on Parallel, Distributed, and Network-Based Processing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ems/2009/3886/0/3886a445",
"title": "Study on Advanced Visualization Tools In Network Monitoring Platform",
"doi": null,
"abstractUrl": "/proceedings-article/ems/2009/3886a445/12OmNscOUdD",
"parentPublication": {
"id": "proceedings/ems/2009/3886/0",
"title": "Computer Modeling and Simulation, UKSIM European Symposium on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/compsym/2016/3438/0/07858557",
"title": "Research on Network Security Visualization under Big Data Environment",
"doi": null,
"abstractUrl": "/proceedings-article/compsym/2016/07858557/12OmNy68ELH",
"parentPublication": {
"id": "proceedings/compsym/2016/3438/0",
"title": "2016 International Computer Symposium (ICS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/trustcom-bigdatase-icess/2017/4906/0/08029552",
"title": "Applications of Visualization Technology for Network Security",
"doi": null,
"abstractUrl": "/proceedings-article/trustcom-bigdatase-icess/2017/08029552/17D45WHONmE",
"parentPublication": {
"id": "proceedings/trustcom-bigdatase-icess/2017/4906/0",
"title": "2017 IEEE Trustcom/BigDataSE/ICESS",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/trustcom-bigdatase/2018/4388/0/438801a639",
"title": "A Full-Scale Security Visualization Effectiveness Measurement and Presentation Approach",
"doi": null,
"abstractUrl": "/proceedings-article/trustcom-bigdatase/2018/438801a639/17D45X2fUHr",
"parentPublication": {
"id": "proceedings/trustcom-bigdatase/2018/4388/0",
"title": "2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/01/09555492",
"title": "Knowledge Rocks: Adding Knowledge Assistance to Visualization Systems",
"doi": null,
"abstractUrl": "/journal/tg/2022/01/09555492/1xjQVW2XkGY",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "05989803",
"articleId": "13rRUxNW1TR",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "06035704",
"articleId": "13rRUwj7cp9",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "12OmNzFdtc9",
"title": "Aug.",
"year": "2012",
"issueNum": "08",
"idPrefix": "tg",
"pubType": "journal",
"volume": "18",
"label": "Aug.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUwj7cp9",
"doi": "10.1109/TVCG.2011.263",
"abstract": "We present an inference-based surface reconstruction algorithm that is capable of identifying objects of interest among a cluttered scene, and reconstructing solid model representations even in the presence of occluded surfaces. Our proposed approach incorporates a predictive modeling framework that uses a set of user-provided models for prior knowledge, and applies this knowledge to the iterative identification and construction process. Our approach uses a local to global construction process guided by rules for fitting high-quality surface patches obtained from these prior models. We demonstrate the application of this algorithm on several example data sets containing heavy clutter and occlusion.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We present an inference-based surface reconstruction algorithm that is capable of identifying objects of interest among a cluttered scene, and reconstructing solid model representations even in the presence of occluded surfaces. Our proposed approach incorporates a predictive modeling framework that uses a set of user-provided models for prior knowledge, and applies this knowledge to the iterative identification and construction process. Our approach uses a local to global construction process guided by rules for fitting high-quality surface patches obtained from these prior models. We demonstrate the application of this algorithm on several example data sets containing heavy clutter and occlusion.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We present an inference-based surface reconstruction algorithm that is capable of identifying objects of interest among a cluttered scene, and reconstructing solid model representations even in the presence of occluded surfaces. Our proposed approach incorporates a predictive modeling framework that uses a set of user-provided models for prior knowledge, and applies this knowledge to the iterative identification and construction process. Our approach uses a local to global construction process guided by rules for fitting high-quality surface patches obtained from these prior models. We demonstrate the application of this algorithm on several example data sets containing heavy clutter and occlusion.",
"title": "Inference-Based Surface Reconstruction of Cluttered Environments",
"normalizedTitle": "Inference-Based Surface Reconstruction of Cluttered Environments",
"fno": "06035704",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Surface Reconstruction",
"Hidden Feature Removal",
"Solid Modelling",
"Construction Process",
"Surface Reconstruction",
"Cluttered Environments",
"Inference Based Surface Reconstruction",
"Solid Model Representations",
"Occluded Surfaces",
"Predictive Modeling",
"User Provided Models",
"Iterative Identification",
"Surface Reconstruction",
"Object Recognition",
"Solid Modeling",
"Shape",
"Surface Treatment",
"Solids",
"Computational Modeling",
"Surface Fitting",
"Three Dimensional Stereo Scene Analysis",
"Object Recognition",
"Segmentation"
],
"authors": [
{
"givenName": "K.",
"surname": "Biggers",
"fullName": "K. Biggers",
"affiliation": "Dept. of Comput. Sci. & Eng., Texas A&M Univ., College Station, TX, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "J.",
"surname": "Keyser",
"fullName": "J. Keyser",
"affiliation": "Dept. of Comput. Sci. & Eng., Texas A&M Univ., College Station, TX, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "08",
"pubDate": "2012-08-01 00:00:00",
"pubType": "trans",
"pages": "1255-1267",
"year": "2012",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/3dv/2015/8332/0/8332a264",
"title": "3D Surface Reconstruction from Point-and-Line Cloud",
"doi": null,
"abstractUrl": "/proceedings-article/3dv/2015/8332a264/12OmNrAMEVf",
"parentPublication": {
"id": "proceedings/3dv/2015/8332/0",
"title": "2015 International Conference on 3D Vision (3DV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2014/5118/0/5118c291",
"title": "Robust Surface Reconstruction via Triple Sparsity",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2014/5118c291/12OmNrIaems",
"parentPublication": {
"id": "proceedings/cvpr/2014/5118/0",
"title": "2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cgiv/2013/5051/0/5051a068",
"title": "Growing Grid-Evolutionary Algorithm for Surface Reconstruction",
"doi": null,
"abstractUrl": "/proceedings-article/cgiv/2013/5051a068/12OmNwogh3R",
"parentPublication": {
"id": "proceedings/cgiv/2013/5051/0",
"title": "2013 10th International Conference Computer Graphics, Imaging and Visualization (CGIV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2010/01/ttp2010010072",
"title": "Differential Geometric Inference in Surface Stereo",
"doi": null,
"abstractUrl": "/journal/tp/2010/01/ttp2010010072/13rRUNvyagg",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2010/04/ttg2010040636",
"title": "Markov Random Field Surface Reconstruction",
"doi": null,
"abstractUrl": "/journal/tg/2010/04/ttg2010040636/13rRUwkxc5l",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2011/05/ttg2011050669",
"title": "Data-Parallel Octrees for Surface Reconstruction",
"doi": null,
"abstractUrl": "/journal/tg/2011/05/ttg2011050669/13rRUxCitJ9",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2004/07/i0878",
"title": "Higher-Order Nonlinear Priors for Surface Reconstruction",
"doi": null,
"abstractUrl": "/journal/tp/2004/07/i0878/13rRUxNEqR8",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2021/2812/0/281200m2971",
"title": "Planar Surface Reconstruction from Sparse Views",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/281200m2971/1BmLppICsyA",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2019/3293/0/329300k0122",
"title": "Deep Geometric Prior for Surface Reconstruction",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2019/329300k0122/1gyrJvG8Kt2",
"parentPublication": {
"id": "proceedings/cvpr/2019/3293/0",
"title": "2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvprw/2020/9360/0/09150931",
"title": "Geometry to the Rescue: 3D Instance Reconstruction from a Cluttered Scene",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2020/09150931/1lPHarhatd6",
"parentPublication": {
"id": "proceedings/cvprw/2020/9360/0",
"title": "2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "06007132",
"articleId": "13rRUygT7y9",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "06060815",
"articleId": "13rRUxASu0I",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "12OmNzFdtc9",
"title": "Aug.",
"year": "2012",
"issueNum": "08",
"idPrefix": "tg",
"pubType": "journal",
"volume": "18",
"label": "Aug.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUxASu0I",
"doi": "10.1109/TVCG.2011.267",
"abstract": "This paper presents a complete and robust solution for dense registration of partial nonrigid shapes. Its novel contributions are founded upon the newly proposed heat kernel coordinates (HKCs) that can accurately position points on the shape, and the priority-vicinity search that ensures geometric compatibility during the registration. HKCs index points by computing heat kernels from multiple sources, and their magnitudes serve as priorities of queuing points in registration. We start with shape features as the sources of heat kernels via feature detection and matching. Following the priority order of HKCs, the dense registration is progressively propagated from feature sources to all points. Our method has a superior indexing ability that can produce dense correspondences with fewer flips. The diffusion nature of HKCs, which can be interpreted as a random walk on a manifold, makes our method robust to noise and small holes avoiding surface surgery and repair. Our method searches correspondence only in a small vicinity of registered points, which significantly improves the time performance. Through comprehensive experiments, our new method has demonstrated its technical soundness and robustness by generating highly compatible dense correspondences.",
"abstracts": [
{
"abstractType": "Regular",
"content": "This paper presents a complete and robust solution for dense registration of partial nonrigid shapes. Its novel contributions are founded upon the newly proposed heat kernel coordinates (HKCs) that can accurately position points on the shape, and the priority-vicinity search that ensures geometric compatibility during the registration. HKCs index points by computing heat kernels from multiple sources, and their magnitudes serve as priorities of queuing points in registration. We start with shape features as the sources of heat kernels via feature detection and matching. Following the priority order of HKCs, the dense registration is progressively propagated from feature sources to all points. Our method has a superior indexing ability that can produce dense correspondences with fewer flips. The diffusion nature of HKCs, which can be interpreted as a random walk on a manifold, makes our method robust to noise and small holes avoiding surface surgery and repair. Our method searches correspondence only in a small vicinity of registered points, which significantly improves the time performance. Through comprehensive experiments, our new method has demonstrated its technical soundness and robustness by generating highly compatible dense correspondences.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "This paper presents a complete and robust solution for dense registration of partial nonrigid shapes. Its novel contributions are founded upon the newly proposed heat kernel coordinates (HKCs) that can accurately position points on the shape, and the priority-vicinity search that ensures geometric compatibility during the registration. HKCs index points by computing heat kernels from multiple sources, and their magnitudes serve as priorities of queuing points in registration. We start with shape features as the sources of heat kernels via feature detection and matching. Following the priority order of HKCs, the dense registration is progressively propagated from feature sources to all points. Our method has a superior indexing ability that can produce dense correspondences with fewer flips. The diffusion nature of HKCs, which can be interpreted as a random walk on a manifold, makes our method robust to noise and small holes avoiding surface surgery and repair. Our method searches correspondence only in a small vicinity of registered points, which significantly improves the time performance. Through comprehensive experiments, our new method has demonstrated its technical soundness and robustness by generating highly compatible dense correspondences.",
"title": "Robust Dense Registration of Partial Nonrigid Shapes",
"normalizedTitle": "Robust Dense Registration of Partial Nonrigid Shapes",
"fno": "06060815",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Solid Modelling",
"Feature Extraction",
"Geometry",
"Image Matching",
"Image Registration",
"Object Detection",
"Random Processes",
"Search Problems",
"Shape Recognition",
"Random Walk",
"Robust Dense Registration",
"Partial Nonrigid Shape",
"Heat Kernel Coordinates",
"Priority Vicinity Search",
"Geometric Compatibility",
"HKC Index Point",
"Magnitude",
"Queuing Point",
"Shape Feature",
"Feature Detection",
"Feature Matching",
"Feature Source Propagation",
"Shape",
"Heating",
"Kernel",
"Manifolds",
"Eigenvalues And Eigenfunctions",
"Feature Extraction",
"Robustness",
"Heat Kernel Coordinates",
"Dense Registration",
"Partial Nonrigid Shape"
],
"authors": [
{
"givenName": null,
"surname": "Tingbo Hou",
"fullName": "Tingbo Hou",
"affiliation": "Dept. of Comput. Sci., Stony Brook Univ., Stony Brook, NY, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": null,
"surname": "Hong Qin",
"fullName": "Hong Qin",
"affiliation": "Dept. of Comput. Sci., Stony Brook Univ., Stony Brook, NY, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "08",
"pubDate": "2012-08-01 00:00:00",
"pubType": "trans",
"pages": "1268-1280",
"year": "2012",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/icpr/2012/2216/0/06460085",
"title": "A hierarchical approach to high-quality partial shape registration",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2012/06460085/12OmNqFrGAA",
"parentPublication": {
"id": "proceedings/icpr/2012/2216/0",
"title": "2012 21st International Conference on Pattern Recognition (ICPR 2012)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/etcs/2010/3987/2/3987b082",
"title": "A Nonrigid Image Registration Approach Based on Cooperative Game Among Pixels",
"doi": null,
"abstractUrl": "/proceedings-article/etcs/2010/3987b082/12OmNvSKO2Z",
"parentPublication": {
"id": "proceedings/etcs/2010/3987/2",
"title": "Education Technology and Computer Science, International Workshop on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2012/1226/0/180P2A30",
"title": "Structure and motion from scene registration",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2012/180P2A30/12OmNx7ouTk",
"parentPublication": {
"id": "proceedings/cvpr/2012/1226/0",
"title": "2012 IEEE Conference on Computer Vision and Pattern Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/dicta/2010/4271/0/4271a546",
"title": "Sparse Update for Loopy Belief Propagation: Fast Dense Registration for Large State Spaces",
"doi": null,
"abstractUrl": "/proceedings-article/dicta/2010/4271a546/12OmNxvO07U",
"parentPublication": {
"id": "proceedings/dicta/2010/4271/0",
"title": "2010 International Conference on Digital Image Computing: Techniques and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/csie/2009/3507/6/3507f239",
"title": "A Hybrid Image Registration for Different Phases of Contrast Enhanced Liver CT Data",
"doi": null,
"abstractUrl": "/proceedings-article/csie/2009/3507f239/12OmNxw5Bol",
"parentPublication": {
"id": null,
"title": null,
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2011/01/ttp2011010158",
"title": "Video Registration Using Dynamic Textures",
"doi": null,
"abstractUrl": "/journal/tp/2011/01/ttp2011010158/13rRUwInvgm",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2006/04/i0643",
"title": "Robust Point Matching for Nonrigid Shapes by Preserving Local Neighborhood Structures",
"doi": null,
"abstractUrl": "/journal/tp/2006/04/i0643/13rRUwhHcKh",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2010/01/ttp2010010087",
"title": "Direct Estimation of Nonrigid Registrations with Image-Based Self-Occlusion Reasoning",
"doi": null,
"abstractUrl": "/journal/tp/2010/01/ttp2010010087/13rRUxNW20p",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2011/08/ttp2011081633",
"title": "Robust Point Set Registration Using Gaussian Mixture Models",
"doi": null,
"abstractUrl": "/journal/tp/2011/08/ttp2011081633/13rRUxjQycY",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvidl/2020/9481/0/948100a021",
"title": "Remote sensing image registration based on fusion of spatial transformation and dense convolution",
"doi": null,
"abstractUrl": "/proceedings-article/cvidl/2020/948100a021/1pbe6YSJZcI",
"parentPublication": {
"id": "proceedings/cvidl/2020/9481/0",
"title": "2020 International Conference on Computer Vision, Image and Deep Learning (CVIDL)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "06035704",
"articleId": "13rRUwj7cp9",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "06143942",
"articleId": "13rRUxC0SvQ",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "12OmNzFdtc9",
"title": "Aug.",
"year": "2012",
"issueNum": "08",
"idPrefix": "tg",
"pubType": "journal",
"volume": "18",
"label": "Aug.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUxC0SvQ",
"doi": "10.1109/TVCG.2012.33",
"abstract": "In this paper, we present a novel technique that allows for the coupled computation and visualization of salient flow structures at interactive frame rates. Our approach is built upon a hierarchical representation of the Finite-time Lyapunov Exponent (FTLE) field, which is adaptively sampled and rendered to meet the need of the current visual setting. The performance of our method allows the user to explore large and complex data sets across scales and to inspect their features at arbitrary resolution. The paper discusses an efficient implementation of this strategy on graphics hardware and provides results for an analytical flow and several CFD simulation data sets.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In this paper, we present a novel technique that allows for the coupled computation and visualization of salient flow structures at interactive frame rates. Our approach is built upon a hierarchical representation of the Finite-time Lyapunov Exponent (FTLE) field, which is adaptively sampled and rendered to meet the need of the current visual setting. The performance of our method allows the user to explore large and complex data sets across scales and to inspect their features at arbitrary resolution. The paper discusses an efficient implementation of this strategy on graphics hardware and provides results for an analytical flow and several CFD simulation data sets.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In this paper, we present a novel technique that allows for the coupled computation and visualization of salient flow structures at interactive frame rates. Our approach is built upon a hierarchical representation of the Finite-time Lyapunov Exponent (FTLE) field, which is adaptively sampled and rendered to meet the need of the current visual setting. The performance of our method allows the user to explore large and complex data sets across scales and to inspect their features at arbitrary resolution. The paper discusses an efficient implementation of this strategy on graphics hardware and provides results for an analytical flow and several CFD simulation data sets.",
"title": "Interactive Computation and Rendering of Finite-Time Lyapunov Exponent Fields",
"normalizedTitle": "Interactive Computation and Rendering of Finite-Time Lyapunov Exponent Fields",
"fno": "06143942",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Lyapunov Methods",
"Computational Fluid Dynamics",
"Flow Visualisation",
"Simulation Data Sets",
"Interactive Computation",
"Finite Time Lyapunov Exponent Fields",
"Coupled Computation",
"Salient Flow Structures Visualization",
"Hierarchical Representation",
"Graphics Hardware",
"Octrees",
"Rendering Computer Graphics",
"Graphics Processing Unit",
"Visualization",
"Transient Analysis",
"Three Dimensional Displays",
"Streaming Data",
"Flow Visualization",
"Vector Field Data",
"GPU And Multicore Architectures",
"Interactive",
"FTLE"
],
"authors": [
{
"givenName": "C.",
"surname": "Garth",
"fullName": "C. Garth",
"affiliation": "Dept. of Comput. Sci., Univ. of California, Davis, CA, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Samer",
"surname": "Barakat",
"fullName": "Samer Barakat",
"affiliation": "Dept. of Comput. Sci., Purdue Univ., West Lafayette, IN, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "X.",
"surname": "Tricoche",
"fullName": "X. Tricoche",
"affiliation": "Dept. of Comput. Sci., Purdue Univ., West Lafayette, IN, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "08",
"pubDate": "2012-08-01 00:00:00",
"pubType": "trans",
"pages": "1368-1380",
"year": "2012",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/snpd/2016/2239/0/07515872",
"title": "An efficient Uniform Integrated Advection algorithm for Finite Time Lyapunov Exponent field computation on GPU and MIC",
"doi": null,
"abstractUrl": "/proceedings-article/snpd/2016/07515872/12OmNAqCtOm",
"parentPublication": {
"id": "proceedings/snpd/2016/2239/0",
"title": "2016 17th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sc/2012/0806/0/1000a102",
"title": "Parallel particle advection and FTLE computation for time-varying flow fields",
"doi": null,
"abstractUrl": "/proceedings-article/sc/2012/1000a102/12OmNBp52zQ",
"parentPublication": {
"id": "proceedings/sc/2012/0806/0",
"title": "SC Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmtma/2010/3962/1/3962a027",
"title": "A Chaotic System with Constant Lyapunov Exponent Spectrum and its Evolvement",
"doi": null,
"abstractUrl": "/proceedings-article/icmtma/2010/3962a027/12OmNCyBXiZ",
"parentPublication": {
"id": "proceedings/icmtma/2010/3962/1",
"title": "2010 International Conference on Measuring Technology and Mechatronics Automation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/avss/2014/4871/0/06918690",
"title": "Local anomaly detection in crowded scenes using Finite-Time Lyapunov Exponent based clustering",
"doi": null,
"abstractUrl": "/proceedings-article/avss/2014/06918690/12OmNvkYxcr",
"parentPublication": {
"id": "proceedings/avss/2014/4871/0",
"title": "2014 International Conference on Advanced Video and Signal Based Surveillance (AVSS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iwcfta/2009/3853/0/3853a404",
"title": "Study on Fault Analysis of Rotor Machinery Using Lyapunov Exponent-Fractal Dimension",
"doi": null,
"abstractUrl": "/proceedings-article/iwcfta/2009/3853a404/12OmNwFicU0",
"parentPublication": {
"id": "proceedings/iwcfta/2009/3853/0",
"title": "Chaos-Fractals Theories and Applications, International Workshop on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icfn/2009/3567/0/3567a122",
"title": "Bifurcation and Lyapunov Exponent in Optical Injected Laser",
"doi": null,
"abstractUrl": "/proceedings-article/icfn/2009/3567a122/12OmNxA3YRT",
"parentPublication": {
"id": "proceedings/icfn/2009/3567/0",
"title": "Future Networks, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icycs/2008/3398/0/3398c973",
"title": "Video Image Targets Detection Based on the Largest Lyapunov Exponent",
"doi": null,
"abstractUrl": "/proceedings-article/icycs/2008/3398c973/12OmNz61d6K",
"parentPublication": {
"id": "proceedings/icycs/2008/3398/0",
"title": "2008 9th International Conference for Young Computer Scientists",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2017/01/07539598",
"title": "Backward Finite-Time Lyapunov Exponents in Inertial Flows",
"doi": null,
"abstractUrl": "/journal/tg/2017/01/07539598/13rRUxC0SOY",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2016/06/07422124",
"title": "Finite-Time Lyapunov Exponents and Lagrangian Coherent Structures in Uncertain Unsteady Flows",
"doi": null,
"abstractUrl": "/journal/tg/2016/06/07422124/13rRUxbTMyV",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2020/01/08805455",
"title": "Accelerated Monte Carlo Rendering of Finite-Time Lyapunov Exponents",
"doi": null,
"abstractUrl": "/journal/tg/2020/01/08805455/1cG4y9tZbPO",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "06060815",
"articleId": "13rRUxASu0I",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "06025349",
"articleId": "13rRUB7a110",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "12OmNzFdtc9",
"title": "Aug.",
"year": "2012",
"issueNum": "08",
"idPrefix": "tg",
"pubType": "journal",
"volume": "18",
"label": "Aug.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUB7a110",
"doi": "10.1109/TVCG.2011.156",
"abstract": "This paper develops a novel surface fitting scheme for automatically reconstructing a genus-0 object into a continuous parametric spline surface. A key contribution for making such a fitting method both practical and accurate is our spherical generalization of the Delaunay configuration B-spline (DCB-spline), a new non-tensor-product spline. In this framework, we efficiently compute Delaunay configurations on sphere by the union of two planar Delaunay configurations. Also, we develop a hierarchical and adaptive method that progressively improves the fitting quality by new knot-insertion strategies guided by surface geometry and fitting error. Within our framework, a genus-0 model can be converted to a single spherical spline representation whose root mean square error is tightly bounded within a user-specified tolerance. The reconstructed continuous representation has many attractive properties such as global smoothness and no auxiliary knots. We conduct several experiments to demonstrate the efficacy of our new approach for reverse engineering and shape modeling.",
"abstracts": [
{
"abstractType": "Regular",
"content": "This paper develops a novel surface fitting scheme for automatically reconstructing a genus-0 object into a continuous parametric spline surface. A key contribution for making such a fitting method both practical and accurate is our spherical generalization of the Delaunay configuration B-spline (DCB-spline), a new non-tensor-product spline. In this framework, we efficiently compute Delaunay configurations on sphere by the union of two planar Delaunay configurations. Also, we develop a hierarchical and adaptive method that progressively improves the fitting quality by new knot-insertion strategies guided by surface geometry and fitting error. Within our framework, a genus-0 model can be converted to a single spherical spline representation whose root mean square error is tightly bounded within a user-specified tolerance. The reconstructed continuous representation has many attractive properties such as global smoothness and no auxiliary knots. We conduct several experiments to demonstrate the efficacy of our new approach for reverse engineering and shape modeling.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "This paper develops a novel surface fitting scheme for automatically reconstructing a genus-0 object into a continuous parametric spline surface. A key contribution for making such a fitting method both practical and accurate is our spherical generalization of the Delaunay configuration B-spline (DCB-spline), a new non-tensor-product spline. In this framework, we efficiently compute Delaunay configurations on sphere by the union of two planar Delaunay configurations. Also, we develop a hierarchical and adaptive method that progressively improves the fitting quality by new knot-insertion strategies guided by surface geometry and fitting error. Within our framework, a genus-0 model can be converted to a single spherical spline representation whose root mean square error is tightly bounded within a user-specified tolerance. The reconstructed continuous representation has many attractive properties such as global smoothness and no auxiliary knots. We conduct several experiments to demonstrate the efficacy of our new approach for reverse engineering and shape modeling.",
"title": "Spherical DCB-Spline Surfaces with Hierarchical and Adaptive Knot Insertion",
"normalizedTitle": "Spherical DCB-Spline Surfaces with Hierarchical and Adaptive Knot Insertion",
"fno": "06025349",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Tensors",
"Computational Geometry",
"Least Mean Squares Methods",
"Mesh Generation",
"Splines Mathematics",
"Surface Fitting",
"Hierarchical Knot Insertion",
"Spherical DCB Spline Surfaces",
"Adaptive Knot Insertion",
"Novel Surface Fitting Scheme",
"Continuous Parametric Spline Surface",
"Delaunay Configuration B Spline",
"Nontensor Product Spline",
"Surface Geometry",
"Genus 0 Model",
"Spherical Spline Representation",
"Reconstructed Continuous Representation",
"Reverse Engineering",
"Shape Modeling",
"Root Mean Square Error",
"Splines Mathematics",
"Surface Reconstruction",
"Polynomials",
"Approximation Methods",
"Surface Treatment",
"Electronic Mail",
"Image Reconstruction",
"Non Tensor Product B Splines",
"Delaunay Configurations",
"Spherical Splines",
"Knot Placement",
"Knot Insertion"
],
"authors": [
{
"givenName": null,
"surname": "Xin Li",
"fullName": "Xin Li",
"affiliation": "Dept. of Electr. & Comput. Eng., Louisiana State Univ., Baton Rouge, LA, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": null,
"surname": "Juan Cao",
"fullName": "Juan Cao",
"affiliation": "Sch. of Math. Sci., Xiamen Univ., Xiamen, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": null,
"surname": "Zhonggui Chen",
"fullName": "Zhonggui Chen",
"affiliation": "Dept. of Comput. Sci., Xiamen Univ., Xiamen, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": null,
"surname": "Hong Qin",
"fullName": "Hong Qin",
"affiliation": "Dept. of Comput. Sci., Stony Brook Univ., Stony Brook, NY, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "08",
"pubDate": "2012-08-01 00:00:00",
"pubType": "trans",
"pages": "1290-1303",
"year": "2012",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/ccc/2002/1468/0/14680024",
"title": "3-MANIFOLD KNOT GENUS is NP-complete",
"doi": null,
"abstractUrl": "/proceedings-article/ccc/2002/14680024/12OmNAolGLQ",
"parentPublication": {
"id": "proceedings/ccc/2002/1468/0",
"title": "Proceedings 17th IEEE Annual Conference on Computational Complexity",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdh/2016/4400/0/4400a272",
"title": "A Balanced Surface Parameterization Method and Its Application to Spline Fitting",
"doi": null,
"abstractUrl": "/proceedings-article/icdh/2016/4400a272/12OmNBC8Awf",
"parentPublication": {
"id": "proceedings/icdh/2016/4400/0",
"title": "2016 6th International Conference on Digital Home (ICDH)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/3dpvt/2006/2825/0/04155783",
"title": "Fast safe spline surrogates for large point clouds",
"doi": null,
"abstractUrl": "/proceedings-article/3dpvt/2006/04155783/12OmNBqdr22",
"parentPublication": {
"id": "proceedings/3dpvt/2006/2825/0",
"title": "Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cadgraphics/2011/4497/0/4497a119",
"title": "The Spherical Images of Triangular Mesh Surfaces",
"doi": null,
"abstractUrl": "/proceedings-article/cadgraphics/2011/4497a119/12OmNCvLY0n",
"parentPublication": {
"id": "proceedings/cadgraphics/2011/4497/0",
"title": "Computer-Aided Design and Computer Graphics, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cw/2009/3791/0/3791a132",
"title": "On Spherical Product Surfaces in E3",
"doi": null,
"abstractUrl": "/proceedings-article/cw/2009/3791a132/12OmNrFkeRT",
"parentPublication": {
"id": "proceedings/cw/2009/3791/0",
"title": "2009 International Conference on CyberWorlds",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/gmai/2007/2901/0/29010085",
"title": "Capturing Outlines of Planar Images by Fuzzy Randomized Knot Insertion to Cubic Spline",
"doi": null,
"abstractUrl": "/proceedings-article/gmai/2007/29010085/12OmNrJiCHB",
"parentPublication": {
"id": "proceedings/gmai/2007/2901/0",
"title": "2007 Geometric Modeling and Imaging: New Advances",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cgi/2000/0643/0/06430163",
"title": "Reconstruction of B-Spline Surfaces from Scattered Data Points",
"doi": null,
"abstractUrl": "/proceedings-article/cgi/2000/06430163/12OmNwnH4Ua",
"parentPublication": {
"id": "proceedings/cgi/2000/0643/0",
"title": "Computer Graphics International Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/1988/0878/0/00028227",
"title": "Calculation method of surface representation using B spline mask",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/1988/00028227/12OmNxWuiip",
"parentPublication": {
"id": "proceedings/icpr/1988/0878/0",
"title": "9th International Conference on Pattern Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icic/2011/688/0/05954508",
"title": "An Improved Algorithm for Surface Fitting Based on B Spline Function",
"doi": null,
"abstractUrl": "/proceedings-article/icic/2011/05954508/12OmNxXCGLN",
"parentPublication": {
"id": "proceedings/icic/2011/688/0",
"title": "2011 Fourth International Conference on Information and Computing (ICIC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pg/2000/0868/0/08680202",
"title": "Subdivision Surface Fitting Using QEM-Based Mesh Simplification and Reconstruction of Approximated B-Spline Surfaces",
"doi": null,
"abstractUrl": "/proceedings-article/pg/2000/08680202/12OmNy49sFt",
"parentPublication": {
"id": "proceedings/pg/2000/0868/0",
"title": "Computer Graphics and Applications, Pacific Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "06143942",
"articleId": "13rRUxC0SvQ",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "06165281",
"articleId": "13rRUILtJm8",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "12OmNzFdtc9",
"title": "Aug.",
"year": "2012",
"issueNum": "08",
"idPrefix": "tg",
"pubType": "journal",
"volume": "18",
"label": "Aug.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUILtJm8",
"doi": "10.1109/TVCG.2012.78",
"abstract": "In this extended version of our Symposium on Computer Animation paper, we describe a domain-decomposition method to simulate articulated deformable characters entirely within a subspace framework. We have added a parallelization and eigendecomposition performance analysis, and several additional examples to the original symposium version. The method supports quasistatic and dynamic deformations, nonlinear kinematics and materials, and can achieve interactive time-stepping rates. To avoid artificial rigidity, or \"locking,” associated with coupling low-rank domain models together with hard constraints, we employ penalty-based coupling forces. The multidomain subspace integrator can simulate deformations efficiently, and exploits efficient subspace-only evaluation of constraint forces between rotated domains using a novel Fast Sandwich Transform (FST). Examples are presented for articulated characters with quasistatic and dynamic deformations, and interactive performance with hundreds of fully coupled modes. Using our method, we have observed speedups of between 3 and 4 orders of magnitude over full-rank, unreduced simulations.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In this extended version of our Symposium on Computer Animation paper, we describe a domain-decomposition method to simulate articulated deformable characters entirely within a subspace framework. We have added a parallelization and eigendecomposition performance analysis, and several additional examples to the original symposium version. The method supports quasistatic and dynamic deformations, nonlinear kinematics and materials, and can achieve interactive time-stepping rates. To avoid artificial rigidity, or \"locking,” associated with coupling low-rank domain models together with hard constraints, we employ penalty-based coupling forces. The multidomain subspace integrator can simulate deformations efficiently, and exploits efficient subspace-only evaluation of constraint forces between rotated domains using a novel Fast Sandwich Transform (FST). Examples are presented for articulated characters with quasistatic and dynamic deformations, and interactive performance with hundreds of fully coupled modes. Using our method, we have observed speedups of between 3 and 4 orders of magnitude over full-rank, unreduced simulations.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In this extended version of our Symposium on Computer Animation paper, we describe a domain-decomposition method to simulate articulated deformable characters entirely within a subspace framework. We have added a parallelization and eigendecomposition performance analysis, and several additional examples to the original symposium version. The method supports quasistatic and dynamic deformations, nonlinear kinematics and materials, and can achieve interactive time-stepping rates. To avoid artificial rigidity, or \"locking,” associated with coupling low-rank domain models together with hard constraints, we employ penalty-based coupling forces. The multidomain subspace integrator can simulate deformations efficiently, and exploits efficient subspace-only evaluation of constraint forces between rotated domains using a novel Fast Sandwich Transform (FST). Examples are presented for articulated characters with quasistatic and dynamic deformations, and interactive performance with hundreds of fully coupled modes. Using our method, we have observed speedups of between 3 and 4 orders of magnitude over full-rank, unreduced simulations.",
"title": "Physics-Based Character Skinning Using Multidomain Subspace Deformations",
"normalizedTitle": "Physics-Based Character Skinning Using Multidomain Subspace Deformations",
"fno": "06165281",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Transforms",
"Computer Animation",
"Deformation",
"Eigenvalues And Eigenfunctions",
"Interactive Systems",
"Parallelization Performance Analysis",
"Physics Based Character Skinning",
"Multidomain Subspace Deformations",
"Domain Decomposition Method",
"Articulated Deformable Character Simulation",
"Eigendecomposition Performance Analysis",
"Computer Animation",
"Quasistatic Deformation",
"Dynamic Deformation",
"Nonlinear Kinematics",
"Interactive Time Stepping Rates",
"Low Rank Domain Model Coupling",
"Hard Constraints",
"Penalty Based Coupling Forces",
"Multidomain Subspace Integrator",
"Subspace Only Evaluation",
"Constraint Forces",
"Fast Sandwich Transform",
"FST",
"Rotated Domains",
"Full Rank Unreduced Simulations",
"Artificial Rigidity Avoidance",
"Deformable Models",
"Couplings",
"Animation",
"Force",
"Computational Modeling",
"Springs",
"Transforms",
"Parallelization",
"Domain Decomposition",
"Deformation",
"Subspace Dynamics",
"Reduced Order Modeling",
"Character Animation"
],
"authors": [
{
"givenName": "T.",
"surname": "Kim",
"fullName": "T. Kim",
"affiliation": "Media Arts & Technol. Program, Univ. of California at Santa Barbara, Santa Barbara, CA, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "D. L.",
"surname": "James",
"fullName": "D. L. James",
"affiliation": "Dept. of Comput. Sci., Cornell Univ., Ithaca, NY, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "08",
"pubDate": "2012-08-01 00:00:00",
"pubType": "trans",
"pages": "1228-1240",
"year": "2012",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/cadgraphics/2011/4497/0/4497a306",
"title": "Lattice-Based Skinning and Deformation for Real-Time Skeleton-Driven Animation",
"doi": null,
"abstractUrl": "/proceedings-article/cadgraphics/2011/4497a306/12OmNBEGYGs",
"parentPublication": {
"id": "proceedings/cadgraphics/2011/4497/0",
"title": "Computer-Aided Design and Computer Graphics, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cgi/2004/2171/0/21710320",
"title": "Animated Sweepers: Keyframed Swept Deformations",
"doi": null,
"abstractUrl": "/proceedings-article/cgi/2004/21710320/12OmNCzb9zV",
"parentPublication": {
"id": "proceedings/cgi/2004/2171/0",
"title": "Proceedings. Computer Graphics International",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdar/1995/7128/1/71280120",
"title": "Segmentation and recognition of handwritten characters using subspace method",
"doi": null,
"abstractUrl": "/proceedings-article/icdar/1995/71280120/12OmNvD8RF6",
"parentPublication": {
"id": "proceedings/icdar/1995/7128/1",
"title": "Proceedings of 3rd International Conference on Document Analysis and Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cso/2010/4030/2/4030b447",
"title": "2D Cartoon Character Deformation by Sketch Skeleton",
"doi": null,
"abstractUrl": "/proceedings-article/cso/2010/4030b447/12OmNxWLTkO",
"parentPublication": {
"id": null,
"title": null,
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2011/03/ttg2011030368",
"title": "Scan-Based Volume Animation Driven by Locally Adaptive Articulated Registrations",
"doi": null,
"abstractUrl": "/journal/tg/2011/03/ttg2011030368/13rRUwInvB0",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/1997/03/v0201",
"title": "Dynamic Free-Form Deformations for Animation Synthesis",
"doi": null,
"abstractUrl": "/journal/tg/1997/03/v0201/13rRUxASuhl",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "06025349",
"articleId": "13rRUB7a110",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "06171182",
"articleId": "13rRUxC0SvR",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "12OmNzFdtc9",
"title": "Aug.",
"year": "2012",
"issueNum": "08",
"idPrefix": "tg",
"pubType": "journal",
"volume": "18",
"label": "Aug.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUxC0SvR",
"doi": "10.1109/TVCG.2012.87",
"abstract": "This paper presents a particle-based model for preserving fluid sheets of animated liquids with an adaptively sampled Fluid-Implicit-Particle (FLIP) method. In our method, we preserve fluid sheets by filling the breaking sheets with particle splitting in the thin regions, and by collapsing them in the deep water. To identify the critically thin parts, we compute the anisotropy of the particle neighborhoods, and use this information as a resampling criterion to reconstruct thin liquid surfaces. Unlike previous approaches, our method does not suffer from diffusive surfaces or complex remeshing operations, and robustly handles topology changes with the use of a meshless representation. We extend the underlying FLIP model with an anisotropic position correction to improve the particle spacing, and adaptive sampling to efficiently perform simulations of larger volumes. Due to the Lagrangian nature of our method, it can be easily implemented and efficiently parallelized. The results show that our method can produce visually complex liquid animations with thin structures and vivid motions.",
"abstracts": [
{
"abstractType": "Regular",
"content": "This paper presents a particle-based model for preserving fluid sheets of animated liquids with an adaptively sampled Fluid-Implicit-Particle (FLIP) method. In our method, we preserve fluid sheets by filling the breaking sheets with particle splitting in the thin regions, and by collapsing them in the deep water. To identify the critically thin parts, we compute the anisotropy of the particle neighborhoods, and use this information as a resampling criterion to reconstruct thin liquid surfaces. Unlike previous approaches, our method does not suffer from diffusive surfaces or complex remeshing operations, and robustly handles topology changes with the use of a meshless representation. We extend the underlying FLIP model with an anisotropic position correction to improve the particle spacing, and adaptive sampling to efficiently perform simulations of larger volumes. Due to the Lagrangian nature of our method, it can be easily implemented and efficiently parallelized. The results show that our method can produce visually complex liquid animations with thin structures and vivid motions.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "This paper presents a particle-based model for preserving fluid sheets of animated liquids with an adaptively sampled Fluid-Implicit-Particle (FLIP) method. In our method, we preserve fluid sheets by filling the breaking sheets with particle splitting in the thin regions, and by collapsing them in the deep water. To identify the critically thin parts, we compute the anisotropy of the particle neighborhoods, and use this information as a resampling criterion to reconstruct thin liquid surfaces. Unlike previous approaches, our method does not suffer from diffusive surfaces or complex remeshing operations, and robustly handles topology changes with the use of a meshless representation. We extend the underlying FLIP model with an anisotropic position correction to improve the particle spacing, and adaptive sampling to efficiently perform simulations of larger volumes. Due to the Lagrangian nature of our method, it can be easily implemented and efficiently parallelized. The results show that our method can produce visually complex liquid animations with thin structures and vivid motions.",
"title": "Preserving Fluid Sheets with Adaptively Sampled Anisotropic Particles",
"normalizedTitle": "Preserving Fluid Sheets with Adaptively Sampled Anisotropic Particles",
"fno": "06171182",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Computational Fluid Dynamics",
"Vivid Motions",
"Fluid Sheets",
"Sampled Anisotropic Particles",
"Particle Based Model",
"Animated Liquids",
"Sampled Fluid Implicit Particle Method",
"Particle Splitting",
"Deep Water",
"Anisotropy",
"Particle Neighborhoods",
"Resampling Criterion",
"Complex Remeshing Operation",
"Topology Change",
"Meshless Representation",
"FLIP Model",
"Anisotropic Position Correction",
"Particle Spacing",
"Adaptive Sampling",
"Lagrangian Nature",
"Complex Liquid Animations",
"Thin Structures",
"Computational Modeling",
"Surface Reconstruction",
"Adaptation Models",
"Interpolation",
"Kernel",
"Mathematical Model",
"Boundary Conditions",
"Adaptive Sampling",
"Physically Based Modeling",
"Liquid Simulation",
"Fluid Implicit Particle Method",
"Thin Fluid Sheets"
],
"authors": [
{
"givenName": "N.",
"surname": "Thurey",
"fullName": "N. Thurey",
"affiliation": "ScanlineVFX GmbH, Munich, Germany",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Ryoichi",
"surname": "Ando",
"fullName": "Ryoichi Ando",
"affiliation": "Grad. Sch. of Design, Kyushu Univ., Fukuoka, Japan",
"__typename": "ArticleAuthorType"
},
{
"givenName": "R.",
"surname": "Tsuruno",
"fullName": "R. Tsuruno",
"affiliation": "Grad. Sch. of Design, Kyushu Univ., Fukuoka, Japan",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "08",
"pubDate": "2012-08-01 00:00:00",
"pubType": "trans",
"pages": "1202-1214",
"year": "2012",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/bibm/2016/1611/0/07822588",
"title": "Numerical assessment of airflow and inhaled particles attributes in obstructed pulmonary system",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2016/07822588/12OmNAle6ia",
"parentPublication": {
"id": "proceedings/bibm/2016/1611/0",
"title": "2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdh/2012/4899/0/4899a074",
"title": "Adaptive Particle Size Setting and Normal Calculation Methods in Fluid Rendering",
"doi": null,
"abstractUrl": "/proceedings-article/icdh/2012/4899a074/12OmNAo45RW",
"parentPublication": {
"id": "proceedings/icdh/2012/4899/0",
"title": "4th International Conference on Digital Home (ICDH)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/visual/1993/3940/0/00398850",
"title": "Visualization of turbulent flow with particles",
"doi": null,
"abstractUrl": "/proceedings-article/visual/1993/00398850/12OmNAolGVS",
"parentPublication": {
"id": "proceedings/visual/1993/3940/0",
"title": "Proceedings Visualization '93",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cgiv/2009/3789/0/3789a038",
"title": "Particle Importance Based Fluid Simulation",
"doi": null,
"abstractUrl": "/proceedings-article/cgiv/2009/3789a038/12OmNAolHa9",
"parentPublication": {
"id": "proceedings/cgiv/2009/3789/0",
"title": "2009 Sixth International Conference on Computer Graphics, Imaging and Visualization",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmtma/2010/3962/3/3962f039",
"title": "Track Calculation and Numerical Simulation on Particles in High Pressure Abrasive Water Jet Nozzle",
"doi": null,
"abstractUrl": "/proceedings-article/icmtma/2010/3962f039/12OmNB8kHRU",
"parentPublication": {
"id": "proceedings/icmtma/2010/3962/3",
"title": "2010 International Conference on Measuring Technology and Mechatronics Automation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cw/2017/2089/0/2089a118",
"title": "Anisotropic Surface Reconstruction for Multiphase Fluids",
"doi": null,
"abstractUrl": "/proceedings-article/cw/2017/2089a118/12OmNCmpcVe",
"parentPublication": {
"id": "proceedings/cw/2017/2089/0",
"title": "2017 International Conference on Cyberworlds (CW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fie/2008/1969/0/04720465",
"title": "Engaging students via student-unique Weekly Assessed Tutorial Sheets: A four year review",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2008/04720465/12OmNz6Apb6",
"parentPublication": {
"id": "proceedings/fie/2008/1969/0",
"title": "2008 38th Annual Frontiers in Education Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccms/2010/3941/1/3941a290",
"title": "A Particle-Based Unified Model for Non-Newtonian Fluid Simulation",
"doi": null,
"abstractUrl": "/proceedings-article/iccms/2010/3941a290/12OmNzzfToR",
"parentPublication": {
"id": "proceedings/iccms/2010/3941/1",
"title": "Computer Modeling and Simulation, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2014/12/06875993",
"title": "Vortex Cores of Inertial Particles",
"doi": null,
"abstractUrl": "/journal/tg/2014/12/06875993/13rRUwbJD4L",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2007/04/v0711",
"title": "Derivative Particles for Simulating Detailed Movements of Fluids",
"doi": null,
"abstractUrl": "/journal/tg/2007/04/v0711/13rRUxYIMUQ",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "06165281",
"articleId": "13rRUILtJm8",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "06171181",
"articleId": "13rRUxlgxTi",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "12OmNzFdtc9",
"title": "Aug.",
"year": "2012",
"issueNum": "08",
"idPrefix": "tg",
"pubType": "journal",
"volume": "18",
"label": "Aug.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUxlgxTi",
"doi": "10.1109/TVCG.2012.86",
"abstract": "We present a multigrid method for solving the linear complementarity problem (LCP) resulting from discretizing the Poisson equation subject to separating solid boundary conditions in an Eulerian liquid simulation's pressure projection step. The method requires only a few small changes to a multigrid solver for linear systems. Our generalized solver is fast enough to handle 3D liquid simulations with separating boundary conditions in practical domain sizes. Previous methods could only handle relatively small 2D domains in reasonable time, because they used expensive quadratic programming (QP) solvers. We demonstrate our technique in several practical scenarios, including nonaxis-aligned containers and moving solids in which the omission of separating boundary conditions results in disturbing artifacts of liquid sticking to solids. Our measurements show, that the convergence rate of our LCP solver is close to that of a standard multigrid solver.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We present a multigrid method for solving the linear complementarity problem (LCP) resulting from discretizing the Poisson equation subject to separating solid boundary conditions in an Eulerian liquid simulation's pressure projection step. The method requires only a few small changes to a multigrid solver for linear systems. Our generalized solver is fast enough to handle 3D liquid simulations with separating boundary conditions in practical domain sizes. Previous methods could only handle relatively small 2D domains in reasonable time, because they used expensive quadratic programming (QP) solvers. We demonstrate our technique in several practical scenarios, including nonaxis-aligned containers and moving solids in which the omission of separating boundary conditions results in disturbing artifacts of liquid sticking to solids. Our measurements show, that the convergence rate of our LCP solver is close to that of a standard multigrid solver.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We present a multigrid method for solving the linear complementarity problem (LCP) resulting from discretizing the Poisson equation subject to separating solid boundary conditions in an Eulerian liquid simulation's pressure projection step. The method requires only a few small changes to a multigrid solver for linear systems. Our generalized solver is fast enough to handle 3D liquid simulations with separating boundary conditions in practical domain sizes. Previous methods could only handle relatively small 2D domains in reasonable time, because they used expensive quadratic programming (QP) solvers. We demonstrate our technique in several practical scenarios, including nonaxis-aligned containers and moving solids in which the omission of separating boundary conditions results in disturbing artifacts of liquid sticking to solids. Our measurements show, that the convergence rate of our LCP solver is close to that of a standard multigrid solver.",
"title": "A Multigrid Fluid Pressure Solver Handling Separating Solid Boundary Conditions",
"normalizedTitle": "A Multigrid Fluid Pressure Solver Handling Separating Solid Boundary Conditions",
"fno": "06171181",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Quadratic Programming",
"Computer Graphics",
"Differential Equations",
"Poisson Equation",
"QP Solvers",
"Multigrid Fluid Pressure Solver",
"Solid Boundary Conditions",
"Linear Complementarity Problem",
"LCP",
"Poisson Equation",
"Eulerian Liquid Simulation",
"Pressure Projection Step",
"3 D Liquid Simulations",
"Quadratic Programming",
"Solids",
"Boundary Conditions",
"Mathematical Model",
"Multigrid Methods",
"Equations",
"Linear Systems",
"Solid Modeling",
"Physics Based Animation",
"Multigrid",
"Boundary Condition",
"Linear Complementarity",
"Fluid Simulation"
],
"authors": [
{
"givenName": "Matthias",
"surname": "Mueller-Fischer",
"fullName": "Matthias Mueller-Fischer",
"affiliation": "NVIDIA PhysX Res., Uerikon, Switzerland",
"__typename": "ArticleAuthorType"
},
{
"givenName": "N.",
"surname": "Chentanez",
"fullName": "N. Chentanez",
"affiliation": "NVIDIA PhysX Res., Bangkok, Thailand",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "08",
"pubDate": "2012-08-01 00:00:00",
"pubType": "trans",
"pages": "1191-1201",
"year": "2012",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/sc/1999/1966/0/19660027",
"title": "Parallel Multigrid Solver for 3D Unstructured Finite Element Problems",
"doi": null,
"abstractUrl": "/proceedings-article/sc/1999/19660027/12OmNAQJzUV",
"parentPublication": {
"id": "proceedings/sc/1999/1966/0",
"title": "SC Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sc/1995/2568/0/25680066",
"title": "A Parallel Incompressible Flow Solver Package with a Parallel Multigrid Elliptic Kernel",
"doi": null,
"abstractUrl": "/proceedings-article/sc/1995/25680066/12OmNC3Xhj8",
"parentPublication": {
"id": "proceedings/sc/1995/2568/0",
"title": "SC Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccms/2010/3941/4/3941d242",
"title": "A Cascadic Multigrid Algorithm for the Double Obstacle Problem",
"doi": null,
"abstractUrl": "/proceedings-article/iccms/2010/3941d242/12OmNviHKgf",
"parentPublication": {
"id": "proceedings/iccms/2010/3941/4",
"title": "Computer Modeling and Simulation, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pdp/2002/1444/0/14440007",
"title": "Beowulf Performance in CFD Multigrid Applications",
"doi": null,
"abstractUrl": "/proceedings-article/pdp/2002/14440007/12OmNwErpNM",
"parentPublication": {
"id": "proceedings/pdp/2002/1444/0",
"title": "10th Euromicro Workshop on Parallel, Distributed and Network-based Processing (EUROMICRO-PDP 2002)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/superc/1995/816/0/01383203",
"title": "A Parallel Incompressible Flow Solver Package with a Parallel Multigrid Elliptic Kernel",
"doi": null,
"abstractUrl": "/proceedings-article/superc/1995/01383203/12OmNwFid6P",
"parentPublication": {
"id": "proceedings/superc/1995/816/0",
"title": "IEEE/ACM SC95 Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/dac/2003/2394/0/23940794",
"title": "An Algebraic Multigrid Solver for Analytical Placement with Layout Based Clustering",
"doi": null,
"abstractUrl": "/proceedings-article/dac/2003/23940794/12OmNx8Oune",
"parentPublication": {
"id": "proceedings/dac/2003/2394/0",
"title": "Design Automation Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sc/2012/0806/0/1000a045",
"title": "Parallel geometric-algebraic multigrid on unstructured forests of octrees",
"doi": null,
"abstractUrl": "/proceedings-article/sc/2012/1000a045/12OmNy7Qfuf",
"parentPublication": {
"id": "proceedings/sc/2012/0806/0",
"title": "SC Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2016/11/07364293",
"title": "Solving the Fluid Pressure Poisson Equation Using Multigrid—Evaluation and Improvements",
"doi": null,
"abstractUrl": "/journal/tg/2016/11/07364293/13rRUwvBy8Y",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2011/11/ttg2011111663",
"title": "A Hexahedral Multigrid Approach for Simulating Cuts in Deformable Objects",
"doi": null,
"abstractUrl": "/journal/tg/2011/11/ttg2011111663/13rRUy0qnGi",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sc/1995/2568/0/01383203",
"title": "A Parallel Incompressible Flow Solver Package with a Parallel Multigrid Elliptic Kernel",
"doi": null,
"abstractUrl": "/proceedings-article/sc/1995/01383203/1D8837kEXOo",
"parentPublication": {
"id": "proceedings/sc/1995/2568/0",
"title": "SC Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "06171182",
"articleId": "13rRUxC0SvR",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "06171183",
"articleId": "13rRUygBw76",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "12OmNzFdtc9",
"title": "Aug.",
"year": "2012",
"issueNum": "08",
"idPrefix": "tg",
"pubType": "journal",
"volume": "18",
"label": "Aug.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUygBw76",
"doi": "10.1109/TVCG.2012.88",
"abstract": "Recent advances in laser scanning technology have made it possible to faithfully scan a real object with tiny geometric details, such as pores and wrinkles. However, a faithful digital model should not only capture static details of the real counterpart but also be able to reproduce the deformed versions of such details. In this paper, we develop a data-driven model that has two components; the first accommodates smooth large-scale deformations and the second captures high-resolution details. Large-scale deformations are based on a nonlinear mapping between sparse control points and bone transformations. A global mapping, however, would fail to synthesize realistic geometries from sparse examples, for highly deformable models with a large range of motion. The key is to train a collection of mappings defined over regions locally in both the geometry and the pose space. Deformable fine-scale details are generated from a second nonlinear mapping between the control points and per-vertex displacements. We apply our modeling scheme to scanned human hand models, scanned face models, face models reconstructed from multiview video sequences, and manually constructed dinosaur models. Experiments show that our deformation models, learned from extremely sparse training data, are effective and robust in synthesizing highly deformable models with rich fine features, for keyframe animation as well as performance-driven animation. We also compare our results with those obtained by alternative techniques.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Recent advances in laser scanning technology have made it possible to faithfully scan a real object with tiny geometric details, such as pores and wrinkles. However, a faithful digital model should not only capture static details of the real counterpart but also be able to reproduce the deformed versions of such details. In this paper, we develop a data-driven model that has two components; the first accommodates smooth large-scale deformations and the second captures high-resolution details. Large-scale deformations are based on a nonlinear mapping between sparse control points and bone transformations. A global mapping, however, would fail to synthesize realistic geometries from sparse examples, for highly deformable models with a large range of motion. The key is to train a collection of mappings defined over regions locally in both the geometry and the pose space. Deformable fine-scale details are generated from a second nonlinear mapping between the control points and per-vertex displacements. We apply our modeling scheme to scanned human hand models, scanned face models, face models reconstructed from multiview video sequences, and manually constructed dinosaur models. Experiments show that our deformation models, learned from extremely sparse training data, are effective and robust in synthesizing highly deformable models with rich fine features, for keyframe animation as well as performance-driven animation. We also compare our results with those obtained by alternative techniques.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Recent advances in laser scanning technology have made it possible to faithfully scan a real object with tiny geometric details, such as pores and wrinkles. However, a faithful digital model should not only capture static details of the real counterpart but also be able to reproduce the deformed versions of such details. In this paper, we develop a data-driven model that has two components; the first accommodates smooth large-scale deformations and the second captures high-resolution details. Large-scale deformations are based on a nonlinear mapping between sparse control points and bone transformations. A global mapping, however, would fail to synthesize realistic geometries from sparse examples, for highly deformable models with a large range of motion. The key is to train a collection of mappings defined over regions locally in both the geometry and the pose space. Deformable fine-scale details are generated from a second nonlinear mapping between the control points and per-vertex displacements. We apply our modeling scheme to scanned human hand models, scanned face models, face models reconstructed from multiview video sequences, and manually constructed dinosaur models. Experiments show that our deformation models, learned from extremely sparse training data, are effective and robust in synthesizing highly deformable models with rich fine features, for keyframe animation as well as performance-driven animation. We also compare our results with those obtained by alternative techniques.",
"title": "Detail-Preserving Controllable Deformation from Sparse Examples",
"normalizedTitle": "Detail-Preserving Controllable Deformation from Sparse Examples",
"fno": "06171183",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Video Signal Processing",
"Computational Geometry",
"Computer Animation",
"Feature Extraction",
"Image Reconstruction",
"Image Sequences",
"Solid Modelling",
"Performance Driven Animation",
"Detail Preserving Controllable Deformation Sparse Examples",
"Laser Scanning Technology",
"Tiny Geometric Details",
"Object Pores",
"Object Wrinkles",
"Faithful Digital Model",
"Static Detail Capture",
"Data Driven Model",
"Smooth Large Scale Deformation",
"High Resolution Detail Capture",
"Nonlinear Mapping",
"Sparse Control Points",
"Bone Transformation",
"Global Mapping",
"Geometry",
"Pose Space",
"Per Vertex Displacement",
"Scanned Human Hand Model",
"Scanned Face Model",
"Face Model Reconstruction",
"Multiview Video Sequence",
"Manually Constructed Dinosaur Model",
"Keyframe Animation",
"Deformable Models",
"Face",
"Training",
"Bones",
"Data Models",
"Geometry",
"Animation",
"CCA Regression",
"Detail Preserving Deformation",
"Controllable Skinning",
"Learning From Sparse Examples"
],
"authors": [
{
"givenName": null,
"surname": "Yue Qi",
"fullName": "Yue Qi",
"affiliation": "State Key Lab. of Virtual Reality Technol. & Syst., Beihang Univ., Beijing, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": null,
"surname": "Ling Zhao",
"fullName": "Ling Zhao",
"affiliation": "State Key Lab. of Virtual Reality Technol. & Syst., Beihang Univ., Beijing, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": null,
"surname": "KangKang Yin",
"fullName": "KangKang Yin",
"affiliation": "Dept. of Comput. Sci., Nat. Univ. of Singapore, Singapore, Singapore",
"__typename": "ArticleAuthorType"
},
{
"givenName": null,
"surname": "Haoda Huang",
"fullName": "Haoda Huang",
"affiliation": "Microsoft Res. Asia, Mountain View, CA, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": null,
"surname": "Yizhou Yu",
"fullName": "Yizhou Yu",
"affiliation": "Univ. of Hong Kong, Hong Kong, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": null,
"surname": "Xin Tong",
"fullName": "Xin Tong",
"affiliation": "Microsoft Res. Asia, Beijing, China",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "08",
"pubDate": "2012-08-01 00:00:00",
"pubType": "trans",
"pages": "1215-1227",
"year": "2012",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/ca/2000/0683/0/06830002",
"title": "Integrated System for Skin Deformation",
"doi": null,
"abstractUrl": "/proceedings-article/ca/2000/06830002/12OmNAtaRXK",
"parentPublication": {
"id": "proceedings/ca/2000/0683/0",
"title": "Computer Animation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cadgraphics/2011/4497/0/4497a306",
"title": "Lattice-Based Skinning and Deformation for Real-Time Skeleton-Driven Animation",
"doi": null,
"abstractUrl": "/proceedings-article/cadgraphics/2011/4497a306/12OmNBEGYGs",
"parentPublication": {
"id": "proceedings/cadgraphics/2011/4497/0",
"title": "Computer-Aided Design and Computer Graphics, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ism/2010/4217/0/4217a236",
"title": "A Hybrid Deformation Model for Virtual Cutting",
"doi": null,
"abstractUrl": "/proceedings-article/ism/2010/4217a236/12OmNBdru9U",
"parentPublication": {
"id": "proceedings/ism/2010/4217/0",
"title": "2010 IEEE International Symposium on Multimedia",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ca/1996/7588/0/75880155",
"title": "Efficient And Accurate Interference Detection For Polynomial Deformation",
"doi": null,
"abstractUrl": "/proceedings-article/ca/1996/75880155/12OmNviHKlH",
"parentPublication": {
"id": "proceedings/ca/1996/7588/0",
"title": "Computer Animation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv-vis/2008/3271/0/3271a129",
"title": "Talking Head - Visualizations & Level of Detail",
"doi": null,
"abstractUrl": "/proceedings-article/iv-vis/2008/3271a129/12OmNwoPttf",
"parentPublication": {
"id": "proceedings/iv-vis/2008/3271/0",
"title": "Visualisation, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pma/2009/3988/0/3988a395",
"title": "Efficient Simulating Interactive Deformation of Virtual Plant",
"doi": null,
"abstractUrl": "/proceedings-article/pma/2009/3988a395/12OmNxE2mNM",
"parentPublication": {
"id": "proceedings/pma/2009/3988/0",
"title": "Plant Growth Modeling and Applications, International Symposium on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cso/2010/4030/2/4030b447",
"title": "2D Cartoon Character Deformation by Sketch Skeleton",
"doi": null,
"abstractUrl": "/proceedings-article/cso/2010/4030b447/12OmNxWLTkO",
"parentPublication": {
"id": null,
"title": null,
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icvrv/2011/4602/0/4602a063",
"title": "Deformation-Aided Virtual Assembly System for Mechanical Structure",
"doi": null,
"abstractUrl": "/proceedings-article/icvrv/2011/4602a063/12OmNxbW4Tv",
"parentPublication": {
"id": "proceedings/icvrv/2011/4602/0",
"title": "2011 International Conference on Virtual Reality and Visualization",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2002/02/v0154",
"title": "An Anatomy-Based Approach to Human Muscle Modeling and Deformation",
"doi": null,
"abstractUrl": "/journal/tg/2002/02/v0154/13rRUIM2VBv",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/2004/03/mcg2004030030",
"title": "Image-Based Surface Detail Transfer",
"doi": null,
"abstractUrl": "/magazine/cg/2004/03/mcg2004030030/13rRUyoyhG5",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "06171181",
"articleId": "13rRUxlgxTi",
"__typename": "AdjacentArticleType"
},
"next": null,
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1zBb6esE5tC",
"doi": "10.1109/TVCG.2021.3114898",
"abstract": "Presents the table of contents for this issue of the publication.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Presents the table of contents for this issue of the publication.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Presents the table of contents for this issue of the publication.",
"title": "Table of Contents",
"normalizedTitle": "Table of Contents",
"fno": "09663068",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [],
"authors": [],
"replicability": null,
"showBuyMe": false,
"showRecommendedArticles": false,
"isOpenAccess": true,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "ii-xi",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [],
"adjacentArticles": {
"previous": null,
"next": {
"fno": "09663062",
"articleId": "1zBaC3IZK9y",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1zBaC3IZK9y",
"doi": "10.1109/TVCG.2021.3114914",
"abstract": "Welcome to the January 2022 issue of the <italic>IEEE Transactions on Visualization and Computer Graphics (TVCG).</italic> This is traditionally the time of the year when we feature the IEEE VIS special issue and this year is no different. But there is one significant difference — IEEE VIS is now fully unified. There is no more IEEE VAST, IEEE InfoVis and IEEE SciVis; there is just IEEE VIS, tiled into six overarching areas: Applications (24 papers), Analytics & Decisions (19), Theoretical & Empirical (24), Representations & Interaction (19), Data Transformations (14) and Systems & Rendering (11). The conference was scheduled to take place in New Orleans (LA) but was moved to a virtual event due to the global coronavirus pandemic. This virtual conference took place from October 24-29, 2021. Contained in this special issue are the top 110 papers selected by the unified program committee from a total of 441 submissions. In addition, this issue also contains the Best Paper of the 2021 IEEE Large Scale Data Analysis and Visualization (LDAV) Symposium and the Best Paper of the 2021 IEEE Symposium on Visualization for Cyber Security (VizSec).",
"abstracts": [
{
"abstractType": "Regular",
"content": "Welcome to the January 2022 issue of the <italic>IEEE Transactions on Visualization and Computer Graphics (TVCG).</italic> This is traditionally the time of the year when we feature the IEEE VIS special issue and this year is no different. But there is one significant difference — IEEE VIS is now fully unified. There is no more IEEE VAST, IEEE InfoVis and IEEE SciVis; there is just IEEE VIS, tiled into six overarching areas: Applications (24 papers), Analytics & Decisions (19), Theoretical & Empirical (24), Representations & Interaction (19), Data Transformations (14) and Systems & Rendering (11). The conference was scheduled to take place in New Orleans (LA) but was moved to a virtual event due to the global coronavirus pandemic. This virtual conference took place from October 24-29, 2021. Contained in this special issue are the top 110 papers selected by the unified program committee from a total of 441 submissions. In addition, this issue also contains the Best Paper of the 2021 IEEE Large Scale Data Analysis and Visualization (LDAV) Symposium and the Best Paper of the 2021 IEEE Symposium on Visualization for Cyber Security (VizSec).",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Welcome to the January 2022 issue of the IEEE Transactions on Visualization and Computer Graphics (TVCG). This is traditionally the time of the year when we feature the IEEE VIS special issue and this year is no different. But there is one significant difference — IEEE VIS is now fully unified. There is no more IEEE VAST, IEEE InfoVis and IEEE SciVis; there is just IEEE VIS, tiled into six overarching areas: Applications (24 papers), Analytics & Decisions (19), Theoretical & Empirical (24), Representations & Interaction (19), Data Transformations (14) and Systems & Rendering (11). The conference was scheduled to take place in New Orleans (LA) but was moved to a virtual event due to the global coronavirus pandemic. This virtual conference took place from October 24-29, 2021. Contained in this special issue are the top 110 papers selected by the unified program committee from a total of 441 submissions. In addition, this issue also contains the Best Paper of the 2021 IEEE Large Scale Data Analysis and Visualization (LDAV) Symposium and the Best Paper of the 2021 IEEE Symposium on Visualization for Cyber Security (VizSec).",
"title": "Message from the Editor-in-Chief",
"normalizedTitle": "Message from the Editor-in-Chief",
"fno": "09663062",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [],
"authors": [
{
"givenName": "Klaus",
"surname": "Mueller",
"fullName": "Klaus Mueller",
"affiliation": "Stony Brook University, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": false,
"showRecommendedArticles": true,
"isOpenAccess": true,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "xii-xii",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "trans/tg/2012/12/ttg20121200ix",
"title": "Message from the Editor-in-Chief",
"doi": null,
"abstractUrl": "/journal/tg/2012/12/ttg20121200ix/13rRUwIF69i",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/ec/2016/01/07423841",
"title": "Message From the Editor-in-Chief",
"doi": null,
"abstractUrl": "/journal/ec/2016/01/07423841/13rRUwgQpvG",
"parentPublication": {
"id": "trans/ec",
"title": "IEEE Transactions on Emerging Topics in Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2014/12/06935055",
"title": "Message from the Editor-in-Chief",
"doi": null,
"abstractUrl": "/journal/tg/2014/12/06935055/13rRUwh80He",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2017/11/08053887",
"title": "Message from the Editor-in-Chief and from the Associate Editor-in-Chief",
"doi": null,
"abstractUrl": "/journal/tg/2017/11/08053887/13rRUxBa56a",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2018/11/08514109",
"title": "Message from the Editor-in-Chief and from the Associate Editor-in-Chief",
"doi": null,
"abstractUrl": "/journal/tg/2018/11/08514109/14M3E12c6Eo",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/11/09927195",
"title": "Message from the Editor-in-Chief and from the Associate Editor-in-Chief",
"doi": null,
"abstractUrl": "/journal/tg/2022/11/09927195/1HGJm87UJvq",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/11/08855103",
"title": "Message from the Editor-in-Chief and from the Associate Editor-in-Chief",
"doi": null,
"abstractUrl": "/journal/tg/2019/11/08855103/1dNHm0Dq8lG",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2020/12/09254193",
"title": "Message from the Editor-in-Chief and from the Associate Editor-in-Chief",
"doi": null,
"abstractUrl": "/journal/tg/2020/12/09254193/1oDXLUaRaDK",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/11/09591457",
"title": "Message from the Editor-in-Chief and from the Associate Editor-in-Chief",
"doi": null,
"abstractUrl": "/journal/tg/2021/11/09591457/1y2Fxh3IZDG",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/01/09663061",
"title": "Preface",
"doi": null,
"abstractUrl": "/journal/tg/2022/01/09663061/1zBb8giCGEU",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09663068",
"articleId": "1zBb6esE5tC",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09663063",
"articleId": "1zBaynLGiHe",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1zBaynLGiHe",
"doi": "10.1109/TVCG.2021.3115333",
"abstract": "We have been honored to oversee the organization of IEEE VIS 2021. This marked the first year in which the SciVis, InfoVis, and VAST conferences were merged into a single, unified IEEE VIS. When we began planning for VIS in 2019, we envisioned a great experience for our community, who would be able to enjoy the innovative scientific program provided by a unified VIS, while delighting in the hospitable and lively atmosphere of New Orleans. But even the best laid plans cannot account for all contingencies. The emergence of the COVID-19 pandemic changed and complicated much in our lives, including the planning for VIS 2021. Moreover, transition to a unified conference was not without its challenges as well. Despite the difficulties, our community showed, once again, its strength and resilience. Our organizing committee created an exciting conference with a rich program full of high-quality research with all challenges being continuously and admirably addressed. As general chairs, our primary responsibility was to watch these wonderful volunteers conduct truly inspiring work under extreme constraints. For this, we are deeply indebted.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We have been honored to oversee the organization of IEEE VIS 2021. This marked the first year in which the SciVis, InfoVis, and VAST conferences were merged into a single, unified IEEE VIS. When we began planning for VIS in 2019, we envisioned a great experience for our community, who would be able to enjoy the innovative scientific program provided by a unified VIS, while delighting in the hospitable and lively atmosphere of New Orleans. But even the best laid plans cannot account for all contingencies. The emergence of the COVID-19 pandemic changed and complicated much in our lives, including the planning for VIS 2021. Moreover, transition to a unified conference was not without its challenges as well. Despite the difficulties, our community showed, once again, its strength and resilience. Our organizing committee created an exciting conference with a rich program full of high-quality research with all challenges being continuously and admirably addressed. As general chairs, our primary responsibility was to watch these wonderful volunteers conduct truly inspiring work under extreme constraints. For this, we are deeply indebted.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We have been honored to oversee the organization of IEEE VIS 2021. This marked the first year in which the SciVis, InfoVis, and VAST conferences were merged into a single, unified IEEE VIS. When we began planning for VIS in 2019, we envisioned a great experience for our community, who would be able to enjoy the innovative scientific program provided by a unified VIS, while delighting in the hospitable and lively atmosphere of New Orleans. But even the best laid plans cannot account for all contingencies. The emergence of the COVID-19 pandemic changed and complicated much in our lives, including the planning for VIS 2021. Moreover, transition to a unified conference was not without its challenges as well. Despite the difficulties, our community showed, once again, its strength and resilience. Our organizing committee created an exciting conference with a rich program full of high-quality research with all challenges being continuously and admirably addressed. As general chairs, our primary responsibility was to watch these wonderful volunteers conduct truly inspiring work under extreme constraints. For this, we are deeply indebted.",
"title": "Welcome",
"normalizedTitle": "Welcome",
"fno": "09663063",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [],
"authors": [
{
"givenName": "Brian",
"surname": "Summa",
"fullName": "Brian Summa",
"affiliation": "Tulane University, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Luis Gustavo",
"surname": "Nonato",
"fullName": "Luis Gustavo Nonato",
"affiliation": "Universidade de Sao Paulo, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": false,
"showRecommendedArticles": true,
"isOpenAccess": true,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "xiii-xiii",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/vis4good/2021/1366/0/136600z006",
"title": "VIS4Good 2021 [Workshop Description and Committees]",
"doi": null,
"abstractUrl": "/proceedings-article/vis4good/2021/136600z006/1yNiRDWGgcE",
"parentPublication": {
"id": "proceedings/vis4good/2021/1366/0",
"title": "2021 IEEE Workshop on Visualization for Social Good (VIS4Good)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/01/09663062",
"title": "Message from the Editor-in-Chief",
"doi": null,
"abstractUrl": "/journal/tg/2022/01/09663062/1zBaC3IZK9y",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/01/09663082",
"title": "VIS 2021 Executive Committee",
"doi": null,
"abstractUrl": "/journal/tg/2022/01/09663082/1zBaJbm09eU",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/01/09663066",
"title": "VIS 2021 Reviewers",
"doi": null,
"abstractUrl": "/journal/tg/2022/01/09663066/1zBaOnEFy6I",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/01/09663064",
"title": "VIS 2021 Program Committee",
"doi": null,
"abstractUrl": "/journal/tg/2022/01/09663064/1zBaReFPWne",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/01/09663080",
"title": "VIS 2021 Steering Committee",
"doi": null,
"abstractUrl": "/journal/tg/2022/01/09663080/1zBaUnoFaDe",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/01/09663070",
"title": "VIS 2021 Best Papers Committee",
"doi": null,
"abstractUrl": "/journal/tg/2022/01/09663070/1zBasw2ZU3K",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/01/09663078",
"title": "VIS 2021 Area Curation Committee",
"doi": null,
"abstractUrl": "/journal/tg/2022/01/09663078/1zBatQHolgs",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/01/09663079",
"title": "VIS 2021 Conference Committee",
"doi": null,
"abstractUrl": "/journal/tg/2022/01/09663079/1zBay2vt8DC",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/01/09663061",
"title": "Preface",
"doi": null,
"abstractUrl": "/journal/tg/2022/01/09663061/1zBb8giCGEU",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09663062",
"articleId": "1zBaC3IZK9y",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09663061",
"articleId": "1zBb8giCGEU",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1zBb8giCGEU",
"doi": "10.1109/TVCG.2021.3114891",
"abstract": "This February 2022 issue of the <italic>IEEE Transactions on Visualization and Computer Graphics (TVCG)</italic> contains the proceedings of IEEE VIS 2021, held online on October 24-29, 2021, with General Chairs from Tulane University and Universidade de Sao Paulo. With IEEE VIS 2021, the conference series is in its 32nd year.",
"abstracts": [
{
"abstractType": "Regular",
"content": "This February 2022 issue of the <italic>IEEE Transactions on Visualization and Computer Graphics (TVCG)</italic> contains the proceedings of IEEE VIS 2021, held online on October 24-29, 2021, with General Chairs from Tulane University and Universidade de Sao Paulo. With IEEE VIS 2021, the conference series is in its 32nd year.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "This February 2022 issue of the IEEE Transactions on Visualization and Computer Graphics (TVCG) contains the proceedings of IEEE VIS 2021, held online on October 24-29, 2021, with General Chairs from Tulane University and Universidade de Sao Paulo. With IEEE VIS 2021, the conference series is in its 32nd year.",
"title": "Preface",
"normalizedTitle": "Preface",
"fno": "09663061",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [],
"authors": [
{
"givenName": "Bongshin",
"surname": "Lee",
"fullName": "Bongshin Lee",
"affiliation": "Microsoft Research, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Silvia",
"surname": "Miksch",
"fullName": "Silvia Miksch",
"affiliation": "Vienna University of Technology (TU Wien), Austria",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Anders",
"surname": "Ynnerman",
"fullName": "Anders Ynnerman",
"affiliation": "Linköping University, Sweden",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Anastasia",
"surname": "Bezerianos",
"fullName": "Anastasia Bezerianos",
"affiliation": "Univ. Paris-Saclay, France",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jian",
"surname": "Chen",
"fullName": "Jian Chen",
"affiliation": "The Ohio State University, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Wei",
"surname": "Chen",
"fullName": "Wei Chen",
"affiliation": "Zhejiang University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Christopher",
"surname": "Collins",
"fullName": "Christopher Collins",
"affiliation": "Ontario Tech University, Canada",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Michael",
"surname": "Gleicher",
"fullName": "Michael Gleicher",
"affiliation": "University of Wisconsin - Madison, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Eduard",
"surname": "Gröller",
"fullName": "Eduard Gröller",
"affiliation": "TU Wien, Austria",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Alexander",
"surname": "Lex",
"fullName": "Alexander Lex",
"affiliation": "University of Utah, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Bernhard",
"surname": "Preim",
"fullName": "Bernhard Preim",
"affiliation": "Otto-von-Guericke-University of Magdeburg, Germany",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jinwook",
"surname": "Seo",
"fullName": "Jinwook Seo",
"affiliation": "Seoul National University, South Korea",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Ruediger",
"surname": "Westermann",
"fullName": "Ruediger Westermann",
"affiliation": "Technical University of Munich, Germany",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jing",
"surname": "Yang",
"fullName": "Jing Yang",
"affiliation": "University of North Carolina at Charlotte, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Xiaoru",
"surname": "Yuan",
"fullName": "Xiaoru Yuan",
"affiliation": "Peking University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Han-Wei",
"surname": "Shen",
"fullName": "Han-Wei Shen",
"affiliation": "The Ohio State University, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jean-Daniel",
"surname": "Fekete",
"fullName": "Jean-Daniel Fekete",
"affiliation": "Inria, France",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Shixia",
"surname": "Liu",
"fullName": "Shixia Liu",
"affiliation": "Tsinghua University, China",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": false,
"showRecommendedArticles": true,
"isOpenAccess": true,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "xiv-xxiii",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "trans/tg/2019/01/08570935",
"title": "Preface",
"doi": null,
"abstractUrl": "/journal/tg/2019/01/08570935/17D45XzbnJm",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2020/01/08930151",
"title": "Preface",
"doi": null,
"abstractUrl": "/journal/tg/2020/01/08930151/1fEi0WcYUXS",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/02/09340112",
"title": "Preface",
"doi": null,
"abstractUrl": "/journal/tg/2021/02/09340112/1qMK1vPtB7i",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/05/09405571",
"title": "Introducing the IEEE Virtual Reality 2021 Special Issue",
"doi": null,
"abstractUrl": "/journal/tg/2021/05/09405571/1sP18PmVuQU",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/11/09591492",
"title": "Message from the ISMAR 2021 Science and Technology Journal Program Chairs and TVCG Guest Editors",
"doi": null,
"abstractUrl": "/journal/tg/2021/11/09591492/1y2FvGMxBuM",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/11/09591457",
"title": "Message from the Editor-in-Chief and from the Associate Editor-in-Chief",
"doi": null,
"abstractUrl": "/journal/tg/2021/11/09591457/1y2Fxh3IZDG",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vis4good/2021/1366/0/136600z006",
"title": "VIS4Good 2021 [Workshop Description and Committees]",
"doi": null,
"abstractUrl": "/proceedings-article/vis4good/2021/136600z006/1yNiRDWGgcE",
"parentPublication": {
"id": "proceedings/vis4good/2021/1366/0",
"title": "2021 IEEE Workshop on Visualization for Social Good (VIS4Good)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/01/09663062",
"title": "Message from the Editor-in-Chief",
"doi": null,
"abstractUrl": "/journal/tg/2022/01/09663062/1zBaC3IZK9y",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/01/09663063",
"title": "Welcome",
"doi": null,
"abstractUrl": "/journal/tg/2022/01/09663063/1zBaynLGiHe",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibe/2021/4261/0/09635338",
"title": "Preface",
"doi": null,
"abstractUrl": "/proceedings-article/bibe/2021/09635338/1zmvltGBJ72",
"parentPublication": {
"id": "proceedings/bibe/2021/4261/0",
"title": "2021 IEEE 21st International Conference on Bioinformatics and Bioengineering (BIBE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09663063",
"articleId": "1zBaynLGiHe",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09663069",
"articleId": "1zBazUF67Is",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1zBazUF67Is",
"doi": "10.1109/TVCG.2021.3114900",
"abstract": "Presents a listing of the IEEE Visualization and Graphics Technical Committee.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Presents a listing of the IEEE Visualization and Graphics Technical Committee.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Presents a listing of the IEEE Visualization and Graphics Technical Committee.",
"title": "IEEE Visualization and Graphics Technical Committee (VGTC): <uri>http://vgtc.org/</uri>",
"normalizedTitle": "IEEE Visualization and Graphics Technical Committee (VGTC): http://vgtc.org/",
"fno": "09663069",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [],
"authors": [],
"replicability": null,
"showBuyMe": false,
"showRecommendedArticles": false,
"isOpenAccess": true,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "xxiv-xxiv",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [],
"adjacentArticles": {
"previous": {
"fno": "09663061",
"articleId": "1zBb8giCGEU",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09663065",
"articleId": "1zBaXZfVCFO",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1zBaXZfVCFO",
"doi": "10.1109/TVCG.2021.3114604",
"abstract": "The 2021 VGTC Visualization Lifetime Achievement Award goes to Jarke van Wijk for his groundbreaking work in the field of data visualization, including fundamentally new approaches for trees, graphs, time series, and flows, for his extensive service to our community, and for his inspiring thoughts on the value of visualization.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The 2021 VGTC Visualization Lifetime Achievement Award goes to Jarke van Wijk for his groundbreaking work in the field of data visualization, including fundamentally new approaches for trees, graphs, time series, and flows, for his extensive service to our community, and for his inspiring thoughts on the value of visualization.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "The 2021 VGTC Visualization Lifetime Achievement Award goes to Jarke van Wijk for his groundbreaking work in the field of data visualization, including fundamentally new approaches for trees, graphs, time series, and flows, for his extensive service to our community, and for his inspiring thoughts on the value of visualization.",
"title": "2021 VGTC Visualization Lifetime Achievement Award—Jarke van Wijk, Eindhoven University of Technology (TU/e)",
"normalizedTitle": "2021 VGTC Visualization Lifetime Achievement Award—Jarke van Wijk, Eindhoven University of Technology (TU/e)",
"fno": "09663065",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [],
"authors": [],
"replicability": null,
"showBuyMe": false,
"showRecommendedArticles": false,
"isOpenAccess": true,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "xxv-xxv",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [],
"adjacentArticles": {
"previous": {
"fno": "09663069",
"articleId": "1zBazUF67Is",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09663057",
"articleId": "1zBb87dswAU",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1zBb87dswAU",
"doi": "10.1109/TVCG.2021.3114602",
"abstract": "The 2021 VGTC Visualization Service Award goes to Loretta Auvil for the dedicated expertise and leadership she has provided to the visualization and visual analytics community through more than two decades of service as a finance chair of the VIS conference as well as her longterm service as finance chair of VGTC.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The 2021 VGTC Visualization Service Award goes to Loretta Auvil for the dedicated expertise and leadership she has provided to the visualization and visual analytics community through more than two decades of service as a finance chair of the VIS conference as well as her longterm service as finance chair of VGTC.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "The 2021 VGTC Visualization Service Award goes to Loretta Auvil for the dedicated expertise and leadership she has provided to the visualization and visual analytics community through more than two decades of service as a finance chair of the VIS conference as well as her longterm service as finance chair of VGTC.",
"title": "2021 VGTC Visualization Service Award—Loretta Auvil, National Center for Supercomputing Applications at the University of Illinois at Urbana Champaign",
"normalizedTitle": "2021 VGTC Visualization Service Award—Loretta Auvil, National Center for Supercomputing Applications at the University of Illinois at Urbana Champaign",
"fno": "09663057",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [],
"authors": [],
"replicability": null,
"showBuyMe": false,
"showRecommendedArticles": false,
"isOpenAccess": true,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "xxvi-xxvi",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [],
"adjacentArticles": {
"previous": {
"fno": "09663065",
"articleId": "1zBaXZfVCFO",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09664413",
"articleId": "1zHDEOUEGVa",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1zHDEOUEGVa",
"doi": "10.1109/TVCG.2021.3114605",
"abstract": "The 2021 VGTC Visualization Significant New Researcher Award goes to Michelle Borkin and Benjamin Bach. Michelle Borkin for her work on visualization memorability, visualization evaluation methods, and their application to astrophysics and medicine. Benjamin Bach for his systematic and theoretically-minded work on temporal visualization, narrative visualization, and immersive visualization.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The 2021 VGTC Visualization Significant New Researcher Award goes to Michelle Borkin and Benjamin Bach. Michelle Borkin for her work on visualization memorability, visualization evaluation methods, and their application to astrophysics and medicine. Benjamin Bach for his systematic and theoretically-minded work on temporal visualization, narrative visualization, and immersive visualization.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "The 2021 VGTC Visualization Significant New Researcher Award goes to Michelle Borkin and Benjamin Bach. Michelle Borkin for her work on visualization memorability, visualization evaluation methods, and their application to astrophysics and medicine. Benjamin Bach for his systematic and theoretically-minded work on temporal visualization, narrative visualization, and immersive visualization.",
"title": "2021 VGTC Visualization Significant New Researcher Award—Michelle Borkin, Northeastern University and Benjamin Bach, University of Edinburgh",
"normalizedTitle": "2021 VGTC Visualization Significant New Researcher Award—Michelle Borkin, Northeastern University and Benjamin Bach, University of Edinburgh",
"fno": "09664413",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [],
"authors": [],
"replicability": null,
"showBuyMe": false,
"showRecommendedArticles": false,
"isOpenAccess": true,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "xxvii-xxviii",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [],
"adjacentArticles": {
"previous": {
"fno": "09663057",
"articleId": "1zBb87dswAU",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09664410",
"articleId": "1zHDIcL2ZOg",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1zHDIcL2ZOg",
"doi": "10.1109/TVCG.2021.3114606",
"abstract": "The 2021 VGTC Visualization Technical Achievement Award goes to Daniel Weiskopf for his research on quantifiable approaches, which has led to deep, powerful, and influential contributions to the visualization of volumes, flows, ensembles, and graphs.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The 2021 VGTC Visualization Technical Achievement Award goes to Daniel Weiskopf for his research on quantifiable approaches, which has led to deep, powerful, and influential contributions to the visualization of volumes, flows, ensembles, and graphs.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "The 2021 VGTC Visualization Technical Achievement Award goes to Daniel Weiskopf for his research on quantifiable approaches, which has led to deep, powerful, and influential contributions to the visualization of volumes, flows, ensembles, and graphs.",
"title": "2021 VGTC Visualization Technical Achievement Award—Daniel Weiskopf, University of Stuttgart, Germany",
"normalizedTitle": "2021 VGTC Visualization Technical Achievement Award—Daniel Weiskopf, University of Stuttgart, Germany",
"fno": "09664410",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [],
"authors": [],
"replicability": null,
"showBuyMe": false,
"showRecommendedArticles": false,
"isOpenAccess": true,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "xxix-xxix",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [],
"adjacentArticles": {
"previous": {
"fno": "09664413",
"articleId": "1zHDEOUEGVa",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09663059",
"articleId": "1zBaY9iZ9bq",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1zBaY9iZ9bq",
"doi": "10.1109/TVCG.2021.3114603",
"abstract": "The 2021 VGTC Visualization Dissertation Award goes to Arjun Srinivasan. Arjun Srinivasan is a member of the Senior Research Staff at Tableau Software in Seattle. He received his Ph.D. from the Georgia Institute of Technology under the supervision of Regents Professor John Stasko. His dissertation bridges the fields of Information Visualization, Human-Computer Interaction, and Natural Language Processing to illustrate the potential of visualization interfaces combining natural language (NL) and direct manipulation (DM) for fluid and expressive human-data interaction experiences.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The 2021 VGTC Visualization Dissertation Award goes to Arjun Srinivasan. Arjun Srinivasan is a member of the Senior Research Staff at Tableau Software in Seattle. He received his Ph.D. from the Georgia Institute of Technology under the supervision of Regents Professor John Stasko. His dissertation bridges the fields of Information Visualization, Human-Computer Interaction, and Natural Language Processing to illustrate the potential of visualization interfaces combining natural language (NL) and direct manipulation (DM) for fluid and expressive human-data interaction experiences.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "The 2021 VGTC Visualization Dissertation Award goes to Arjun Srinivasan. Arjun Srinivasan is a member of the Senior Research Staff at Tableau Software in Seattle. He received his Ph.D. from the Georgia Institute of Technology under the supervision of Regents Professor John Stasko. His dissertation bridges the fields of Information Visualization, Human-Computer Interaction, and Natural Language Processing to illustrate the potential of visualization interfaces combining natural language (NL) and direct manipulation (DM) for fluid and expressive human-data interaction experiences.",
"title": "2021 VGTC Visualization Dissertation Award—Arjun Srinivasan, Tableau Software",
"normalizedTitle": "2021 VGTC Visualization Dissertation Award—Arjun Srinivasan, Tableau Software",
"fno": "09663059",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [],
"authors": [],
"replicability": null,
"showBuyMe": false,
"showRecommendedArticles": false,
"isOpenAccess": true,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "xxx-xxx",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [],
"adjacentArticles": {
"previous": {
"fno": "09664410",
"articleId": "1zHDIcL2ZOg",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09663079",
"articleId": "1zBay2vt8DC",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1zBay2vt8DC",
"doi": "10.1109/TVCG.2021.3114894",
"abstract": "Presents a listing of the VIS 2021 Conference Committee.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Presents a listing of the VIS 2021 Conference Committee.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Presents a listing of the VIS 2021 Conference Committee.",
"title": "VIS 2021 Conference Committee",
"normalizedTitle": "VIS 2021 Conference Committee",
"fno": "09663079",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [],
"authors": [],
"replicability": null,
"showBuyMe": false,
"showRecommendedArticles": false,
"isOpenAccess": true,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "xxxi-xxxiii",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [],
"adjacentArticles": {
"previous": {
"fno": "09663059",
"articleId": "1zBaY9iZ9bq",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09663080",
"articleId": "1zBaUnoFaDe",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1zBaUnoFaDe",
"doi": "10.1109/TVCG.2021.3125547",
"abstract": "Presents a listing of the VIS 2021 Steering Committee.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Presents a listing of the VIS 2021 Steering Committee.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Presents a listing of the VIS 2021 Steering Committee.",
"title": "VIS 2021 Steering Committee",
"normalizedTitle": "VIS 2021 Steering Committee",
"fno": "09663080",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [],
"authors": [],
"replicability": null,
"showBuyMe": false,
"showRecommendedArticles": false,
"isOpenAccess": true,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "xxxiv-xxxiv",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [],
"adjacentArticles": {
"previous": {
"fno": "09663079",
"articleId": "1zBay2vt8DC",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09663082",
"articleId": "1zBaJbm09eU",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1zBaJbm09eU",
"doi": "10.1109/TVCG.2021.3125595",
"abstract": "Presents a listing of the VIS 2021 Executive Committee.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Presents a listing of the VIS 2021 Executive Committee.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Presents a listing of the VIS 2021 Executive Committee.",
"title": "VIS 2021 Executive Committee",
"normalizedTitle": "VIS 2021 Executive Committee",
"fno": "09663082",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [],
"authors": [],
"replicability": null,
"showBuyMe": false,
"showRecommendedArticles": false,
"isOpenAccess": true,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "xxxv-xxxv",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [],
"adjacentArticles": {
"previous": {
"fno": "09663080",
"articleId": "1zBaUnoFaDe",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09663078",
"articleId": "1zBatQHolgs",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1zBatQHolgs",
"doi": "10.1109/TVCG.2021.3125551",
"abstract": "Presents a listing of the VIS 2021 Area Curation Committee.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Presents a listing of the VIS 2021 Area Curation Committee.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Presents a listing of the VIS 2021 Area Curation Committee.",
"title": "VIS 2021 Area Curation Committee",
"normalizedTitle": "VIS 2021 Area Curation Committee",
"fno": "09663078",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [],
"authors": [],
"replicability": null,
"showBuyMe": false,
"showRecommendedArticles": false,
"isOpenAccess": true,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "xxxvi-xxxvi",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [],
"adjacentArticles": {
"previous": {
"fno": "09663082",
"articleId": "1zBaJbm09eU",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09663064",
"articleId": "1zBaReFPWne",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1zBaReFPWne",
"doi": "10.1109/TVCG.2021.3114915",
"abstract": "Presents a listing of the VIS 2021 Program Committee.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Presents a listing of the VIS 2021 Program Committee.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Presents a listing of the VIS 2021 Program Committee.",
"title": "VIS 2021 Program Committee",
"normalizedTitle": "VIS 2021 Program Committee",
"fno": "09663064",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [],
"authors": [],
"replicability": null,
"showBuyMe": false,
"showRecommendedArticles": false,
"isOpenAccess": true,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "xxxvii-xl",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [],
"adjacentArticles": {
"previous": {
"fno": "09663078",
"articleId": "1zBatQHolgs",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09663070",
"articleId": "1zBasw2ZU3K",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1zBasw2ZU3K",
"doi": "10.1109/TVCG.2021.3114935",
"abstract": "Presents a listing of the VIS 2021 Best Papers Committee.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Presents a listing of the VIS 2021 Best Papers Committee.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Presents a listing of the VIS 2021 Best Papers Committee.",
"title": "VIS 2021 Best Papers Committee",
"normalizedTitle": "VIS 2021 Best Papers Committee",
"fno": "09663070",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [],
"authors": [],
"replicability": null,
"showBuyMe": false,
"showRecommendedArticles": false,
"isOpenAccess": true,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "xli-xliii",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [],
"adjacentArticles": {
"previous": {
"fno": "09663064",
"articleId": "1zBaReFPWne",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09663066",
"articleId": "1zBaOnEFy6I",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1zBaOnEFy6I",
"doi": "10.1109/TVCG.2021.3114913",
"abstract": "Presents a listing of the VIS 2021 reviewers.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Presents a listing of the VIS 2021 reviewers.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Presents a listing of the VIS 2021 reviewers.",
"title": "VIS 2021 Reviewers",
"normalizedTitle": "VIS 2021 Reviewers",
"fno": "09663066",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [],
"authors": [],
"replicability": null,
"showBuyMe": false,
"showRecommendedArticles": false,
"isOpenAccess": true,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "xliv-xlviii",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [],
"adjacentArticles": {
"previous": {
"fno": "09663070",
"articleId": "1zBasw2ZU3K",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552242",
"articleId": "1xic4WSUlKE",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xic4WSUlKE",
"doi": "10.1109/TVCG.2021.3114773",
"abstract": "Undirected graphs are frequently used to model phenomena that deal with interacting objects, such as social networks, brain activity and communication networks. The topology of an undirected graph <inline-formula><tex-math notation=\"LaTeX\">Z_$G$_Z</tex-math></inline-formula> can be captured by an adjacency matrix; this matrix in turn can be visualized directly to give insight into the graph structure. Which visual patterns appear in such a matrix visualization crucially depends on the <italic>ordering</italic> of its rows and columns. Formally defining the quality of an ordering and then automatically computing a high-quality ordering are both challenging problems; however, effective heuristics exist and are used in practice.</p> <p>Often, graphs do not exist in isolation but as part of a collection of graphs on the same set of vertices, for example, brain scans over time or of different people. To visualize such graph collections, we need a <italic>single</italic> ordering that works well for all matrices <italic>simultaneously</italic>. The current state-of-the-art solves this problem by taking a (weighted) union over all graphs and applying existing heuristics. However, this union leads to a loss of information, specifically in those parts of the graphs which are different. We propose a <italic>collection-aware</italic> approach to avoid this loss of information and apply it to two popular heuristic methods: leaf order and barycenter.</p> <p>The de-facto standard computational quality metrics for matrix ordering capture only block-diagonal patterns (cliques). Instead, we propose to use <italic>Moran's</italic> <inline-formula><tex-math notation=\"LaTeX\">Z_$I$_Z</tex-math></inline-formula>, a spatial auto-correlation metric, which captures the full range of established patterns. Moran's <inline-formula><tex-math notation=\"LaTeX\">Z_$I$_Z</tex-math></inline-formula> refines previously proposed stress measures. Furthermore, the popular leaf order method heuristically optimizes a similar measure which further supports the use of Moran's <inline-formula><tex-math notation=\"LaTeX\">Z_$I$_Z</tex-math></inline-formula> in this context. An ordering that maximizes Moran's <inline-formula><tex-math notation=\"LaTeX\">Z_$I$_Z</tex-math></inline-formula> can be computed via solutions to the Traveling Salesperson Problem (TSP); orderings that approximate the optimal ordering can be computed more efficiently, using any of the approximation algorithms for metric TSP.</p> <p>We evaluated our methods for simultaneous orderings on real-world datasets using Moran's <inline-formula><tex-math notation=\"LaTeX\">Z_$I$_Z</tex-math></inline-formula> as the quality metric. Our results show that our collection-aware approach matches or improves performance compared to the union approach, depending on the similarity of the graphs in the collection. Specifically, our Moran's <inline-formula><tex-math notation=\"LaTeX\">Z_$I$_Z</tex-math></inline-formula>-based collection-aware leaf order implementation consistently outperforms other implementations. Our collection-aware implementations carry no significant additional computational costs.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Undirected graphs are frequently used to model phenomena that deal with interacting objects, such as social networks, brain activity and communication networks. The topology of an undirected graph <inline-formula><tex-math notation=\"LaTeX\">$G$</tex-math><alternatives><graphic position=\"float\" orientation=\"portrait\" xlink:href=\"28tvcg01-beusekom-3114773-eqinline-1-small.tif\"/></alternatives></inline-formula> can be captured by an adjacency matrix; this matrix in turn can be visualized directly to give insight into the graph structure. Which visual patterns appear in such a matrix visualization crucially depends on the <italic>ordering</italic> of its rows and columns. Formally defining the quality of an ordering and then automatically computing a high-quality ordering are both challenging problems; however, effective heuristics exist and are used in practice.</p> <p>Often, graphs do not exist in isolation but as part of a collection of graphs on the same set of vertices, for example, brain scans over time or of different people. To visualize such graph collections, we need a <italic>single</italic> ordering that works well for all matrices <italic>simultaneously</italic>. The current state-of-the-art solves this problem by taking a (weighted) union over all graphs and applying existing heuristics. However, this union leads to a loss of information, specifically in those parts of the graphs which are different. We propose a <italic>collection-aware</italic> approach to avoid this loss of information and apply it to two popular heuristic methods: leaf order and barycenter.</p> <p>The de-facto standard computational quality metrics for matrix ordering capture only block-diagonal patterns (cliques). Instead, we propose to use <italic>Moran's</italic> <inline-formula><tex-math notation=\"LaTeX\">$I$</tex-math><alternatives><graphic position=\"float\" orientation=\"portrait\" xlink:href=\"28tvcg01-beusekom-3114773-eqinline-2-small.tif\"/></alternatives></inline-formula>, a spatial auto-correlation metric, which captures the full range of established patterns. Moran's <inline-formula><tex-math notation=\"LaTeX\">$I$</tex-math><alternatives><graphic position=\"float\" orientation=\"portrait\" xlink:href=\"28tvcg01-beusekom-3114773-eqinline-3-small.tif\"/></alternatives></inline-formula> refines previously proposed stress measures. Furthermore, the popular leaf order method heuristically optimizes a similar measure which further supports the use of Moran's <inline-formula><tex-math notation=\"LaTeX\">$I$</tex-math><alternatives><graphic position=\"float\" orientation=\"portrait\" xlink:href=\"28tvcg01-beusekom-3114773-eqinline-4-small.tif\"/></alternatives></inline-formula> in this context. An ordering that maximizes Moran's <inline-formula><tex-math notation=\"LaTeX\">$I$</tex-math><alternatives><graphic position=\"float\" orientation=\"portrait\" xlink:href=\"28tvcg01-beusekom-3114773-eqinline-5-small.tif\"/></alternatives></inline-formula> can be computed via solutions to the Traveling Salesperson Problem (TSP); orderings that approximate the optimal ordering can be computed more efficiently, using any of the approximation algorithms for metric TSP.</p> <p>We evaluated our methods for simultaneous orderings on real-world datasets using Moran's <inline-formula><tex-math notation=\"LaTeX\">$I$</tex-math><alternatives><graphic position=\"float\" orientation=\"portrait\" xlink:href=\"28tvcg01-beusekom-3114773-eqinline-6-small.tif\"/></alternatives></inline-formula> as the quality metric. Our results show that our collection-aware approach matches or improves performance compared to the union approach, depending on the similarity of the graphs in the collection. Specifically, our Moran's <inline-formula><tex-math notation=\"LaTeX\">$I$</tex-math><alternatives><graphic position=\"float\" orientation=\"portrait\" xlink:href=\"28tvcg01-beusekom-3114773-eqinline-7-small.tif\"/></alternatives></inline-formula>-based collection-aware leaf order implementation consistently outperforms other implementations. Our collection-aware implementations carry no significant additional computational costs.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Undirected graphs are frequently used to model phenomena that deal with interacting objects, such as social networks, brain activity and communication networks. The topology of an undirected graph - can be captured by an adjacency matrix; this matrix in turn can be visualized directly to give insight into the graph structure. Which visual patterns appear in such a matrix visualization crucially depends on the ordering of its rows and columns. Formally defining the quality of an ordering and then automatically computing a high-quality ordering are both challenging problems; however, effective heuristics exist and are used in practice. Often, graphs do not exist in isolation but as part of a collection of graphs on the same set of vertices, for example, brain scans over time or of different people. To visualize such graph collections, we need a single ordering that works well for all matrices simultaneously. The current state-of-the-art solves this problem by taking a (weighted) union over all graphs and applying existing heuristics. However, this union leads to a loss of information, specifically in those parts of the graphs which are different. We propose a collection-aware approach to avoid this loss of information and apply it to two popular heuristic methods: leaf order and barycenter. The de-facto standard computational quality metrics for matrix ordering capture only block-diagonal patterns (cliques). Instead, we propose to use Moran's -, a spatial auto-correlation metric, which captures the full range of established patterns. Moran's - refines previously proposed stress measures. Furthermore, the popular leaf order method heuristically optimizes a similar measure which further supports the use of Moran's - in this context. An ordering that maximizes Moran's - can be computed via solutions to the Traveling Salesperson Problem (TSP); orderings that approximate the optimal ordering can be computed more efficiently, using any of the approximation algorithms for metric TSP. We evaluated our methods for simultaneous orderings on real-world datasets using Moran's - as the quality metric. Our results show that our collection-aware approach matches or improves performance compared to the union approach, depending on the similarity of the graphs in the collection. Specifically, our Moran's --based collection-aware leaf order implementation consistently outperforms other implementations. Our collection-aware implementations carry no significant additional computational costs.",
"title": "Simultaneous Matrix Orderings for Graph Collections",
"normalizedTitle": "Simultaneous Matrix Orderings for Graph Collections",
"fno": "09552242",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Visualization",
"Measurement",
"Tools",
"Symmetric Matrices",
"Current Measurement",
"Standards",
"Social Networking Online",
"Matrix Ordering",
"Graph Visualization",
"Algorithms",
"Quality Measures"
],
"authors": [
{
"givenName": "Nathan",
"surname": "van Beusekom",
"fullName": "Nathan van Beusekom",
"affiliation": "TU Eindhoven, the Netherlands",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Wouter",
"surname": "Meulemans",
"fullName": "Wouter Meulemans",
"affiliation": "TU Eindhoven, the Netherlands",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Bettina",
"surname": "Speckmann",
"fullName": "Bettina Speckmann",
"affiliation": "TU Eindhoven, the Netherlands",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "1-10",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "trans/tp/2019/05/08344546",
"title": "What Makes Objects Similar: A Unified Multi-Metric Learning Approach",
"doi": null,
"abstractUrl": "/journal/tp/2019/05/08344546/13rRUNvgyXK",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tc/2019/04/08494787",
"title": "Better Circuits for Binary Polynomial Multiplication",
"doi": null,
"abstractUrl": "/journal/tc/2019/04/08494787/14s8M4Sn2IE",
"parentPublication": {
"id": "trans/tc",
"title": "IEEE Transactions on Computers",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/td/2018/12/08392762",
"title": "Competitiveness of a Non-Linear Block-Space GPU Thread Map for Simplex Domains",
"doi": null,
"abstractUrl": "/journal/td/2018/12/08392762/17D45XzbnJ8",
"parentPublication": {
"id": "trans/td",
"title": "IEEE Transactions on Parallel & Distributed Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2023/01/09681162",
"title": "Point Cloud Sampling via Graph Balancing and Gershgorin Disc Alignment",
"doi": null,
"abstractUrl": "/journal/tp/2023/01/09681162/1A8c6sY0Afe",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2023/01/09712412",
"title": "Centerless Clustering",
"doi": null,
"abstractUrl": "/journal/tp/2023/01/09712412/1AZKZVM8b84",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2023/06/09774007",
"title": "Graph Stream Sketch: Summarizing Graph Streams With High Speed and Accuracy",
"doi": null,
"abstractUrl": "/journal/tk/2023/06/09774007/1DjDnjq9sGI",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2022/04/09109708",
"title": "Unsupervised Large Graph Embedding Based on Balanced and Hierarchical K-Means",
"doi": null,
"abstractUrl": "/journal/tk/2022/04/09109708/1kpEsyACWGs",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2022/01/09134812",
"title": "Robust Bi-Stochastic Graph Regularized Matrix Factorization for Data Clustering",
"doi": null,
"abstractUrl": "/journal/tp/2022/01/09134812/1lgLpXeYP7y",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2022/09/09405430",
"title": "Learning Log-Determinant Divergences for Positive Definite Matrices",
"doi": null,
"abstractUrl": "/journal/tp/2022/09/09405430/1sP16sJ7CCs",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2022/10/09463735",
"title": "Signed Graph Metric Learning via Gershgorin Disc Perfect Alignment",
"doi": null,
"abstractUrl": "/journal/tp/2022/10/09463735/1uFxm1okYhO",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09663066",
"articleId": "1zBaOnEFy6I",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552903",
"articleId": "1xibWJujrkk",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBaPpC5Ne0",
"name": "ttg202201-09552242s1-supp1-3114773.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552242s1-supp1-3114773.pdf",
"extension": "pdf",
"size": "5.57 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xibWJujrkk",
"doi": "10.1109/TVCG.2021.3114797",
"abstract": "In this design study, we present IRVINE, a Visual Analytics (VA) system, which facilitates the analysis of acoustic data to detect and understand previously unknown errors in the manufacturing of electrical engines. In serial manufacturing processes, signatures from acoustic data provide valuable information on how the relationship between multiple produced engines serves to detect and understand previously unknown errors. To analyze such signatures, IRVINE leverages interactive clustering and data labeling techniques, allowing users to analyze clusters of engines with similar signatures, drill down to groups of engines, and select an engine of interest. Furthermore, IRVINE allows to assign labels to engines and clusters and annotate the cause of an error in the acoustic raw measurement of an engine. Since labels and annotations represent valuable knowledge, they are conserved in a knowledge database to be available for other stakeholders. We contribute a design study, where we developed IRVINE in four main iterations with engineers from a company in the automotive sector. To validate IRVINE, we conducted a field study with six domain experts. Our results suggest a high usability and usefulness of IRVINE as part of the improvement of a real-world manufacturing process. Specifically, with IRVINE domain experts were able to label and annotate produced electrical engines more than 30% faster.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In this design study, we present IRVINE, a Visual Analytics (VA) system, which facilitates the analysis of acoustic data to detect and understand previously unknown errors in the manufacturing of electrical engines. In serial manufacturing processes, signatures from acoustic data provide valuable information on how the relationship between multiple produced engines serves to detect and understand previously unknown errors. To analyze such signatures, IRVINE leverages interactive clustering and data labeling techniques, allowing users to analyze clusters of engines with similar signatures, drill down to groups of engines, and select an engine of interest. Furthermore, IRVINE allows to assign labels to engines and clusters and annotate the cause of an error in the acoustic raw measurement of an engine. Since labels and annotations represent valuable knowledge, they are conserved in a knowledge database to be available for other stakeholders. We contribute a design study, where we developed IRVINE in four main iterations with engineers from a company in the automotive sector. To validate IRVINE, we conducted a field study with six domain experts. Our results suggest a high usability and usefulness of IRVINE as part of the improvement of a real-world manufacturing process. Specifically, with IRVINE domain experts were able to label and annotate produced electrical engines more than 30% faster.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In this design study, we present IRVINE, a Visual Analytics (VA) system, which facilitates the analysis of acoustic data to detect and understand previously unknown errors in the manufacturing of electrical engines. In serial manufacturing processes, signatures from acoustic data provide valuable information on how the relationship between multiple produced engines serves to detect and understand previously unknown errors. To analyze such signatures, IRVINE leverages interactive clustering and data labeling techniques, allowing users to analyze clusters of engines with similar signatures, drill down to groups of engines, and select an engine of interest. Furthermore, IRVINE allows to assign labels to engines and clusters and annotate the cause of an error in the acoustic raw measurement of an engine. Since labels and annotations represent valuable knowledge, they are conserved in a knowledge database to be available for other stakeholders. We contribute a design study, where we developed IRVINE in four main iterations with engineers from a company in the automotive sector. To validate IRVINE, we conducted a field study with six domain experts. Our results suggest a high usability and usefulness of IRVINE as part of the improvement of a real-world manufacturing process. Specifically, with IRVINE domain experts were able to label and annotate produced electrical engines more than 30% faster.",
"title": "IRVINE: A Design Study on Analyzing Correlation Patterns of Electrical Engines",
"normalizedTitle": "IRVINE: A Design Study on Analyzing Correlation Patterns of Electrical Engines",
"fno": "09552903",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Engines",
"Acoustics",
"Labeling",
"Annotations",
"Task Analysis",
"Automotive Engineering",
"Data Visualization",
"Design Study",
"Interactive Labeling",
"Interactive Clustering",
"H 5 2 Information Interfaces And Presentation",
"User Interfaces Graphical User Interfaces GUI",
"User Centered Design"
],
"authors": [
{
"givenName": "Joscha",
"surname": "Eirich",
"fullName": "Joscha Eirich",
"affiliation": "University of Bamberg, Germany",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jakob",
"surname": "Bonart",
"fullName": "Jakob Bonart",
"affiliation": "Fraunhofer IWU, Germany",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Dominik",
"surname": "Jäckle",
"fullName": "Dominik Jäckle",
"affiliation": "BMW Group, Germany",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Michael",
"surname": "Sedlmair",
"fullName": "Michael Sedlmair",
"affiliation": "University of Stuttgart, Germany",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Ute",
"surname": "Schmid",
"fullName": "Ute Schmid",
"affiliation": "University of Bamberg, Germany",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Kai",
"surname": "Fischbach",
"fullName": "Kai Fischbach",
"affiliation": "University of Bamberg, Germany",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Tobias",
"surname": "Schreck",
"fullName": "Tobias Schreck",
"affiliation": "Graz University of Technology, Austria",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jürgen",
"surname": "Bernard",
"fullName": "Jürgen Bernard",
"affiliation": "University of Zurich, Switzerland",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "11-21",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/ipccc/2008/3368/0/04745108",
"title": "Detection of Worm Propagation Engines in the System Call Domain using Colored Petri Nets",
"doi": null,
"abstractUrl": "/proceedings-article/ipccc/2008/04745108/12OmNAHmOt8",
"parentPublication": {
"id": "proceedings/ipccc/2008/3368/0",
"title": "2008 IEEE International Performance Computing and Communications Conference (IPCCC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmtma/2011/4296/3/4296e683",
"title": "The Application of Correlation Dimensions of Vibration Signals in Analysis of the Technological State of Diesel Engines",
"doi": null,
"abstractUrl": "/proceedings-article/icmtma/2011/4296e683/12OmNCfjeuL",
"parentPublication": {
"id": "proceedings/icmtma/2011/4296/3",
"title": "2011 Third International Conference on Measuring Technology and Mechatronics Automation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icimp/2008/3189/0/3189a161",
"title": "An Evaluation of Major Image Search Engines on Various Query Topics",
"doi": null,
"abstractUrl": "/proceedings-article/icimp/2008/3189a161/12OmNs59K35",
"parentPublication": {
"id": "proceedings/icimp/2008/3189/0",
"title": "Internet Monitoring and Protection, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icac/2004/2114/0/01301388",
"title": "Ontology-based correlation engines",
"doi": null,
"abstractUrl": "/proceedings-article/icac/2004/01301388/12OmNy4IF7v",
"parentPublication": {
"id": "proceedings/icac/2004/2114/0",
"title": "Autonomic Computing, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/acii/2013/5048/0/5048a454",
"title": "Parameter Optimization Issues for Cross-corpora Emotion Classification",
"doi": null,
"abstractUrl": "/proceedings-article/acii/2013/5048a454/12OmNyUFfW4",
"parentPublication": {
"id": "proceedings/acii/2013/5048/0",
"title": "2013 Humaine Association Conference on Affective Computing and Intelligent Interaction (ACII)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/si/2013/05/06275517",
"title": "Parametric DFM Solution for Analog Circuits: Electrical-Driven Hotspot Detection, Analysis, and Correction Flow",
"doi": null,
"abstractUrl": "/journal/si/2013/05/06275517/13rRUwfI0ND",
"parentPublication": {
"id": "trans/si",
"title": "IEEE Transactions on Very Large Scale Integration (VLSI) Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/2022/02/09723551",
"title": "ManEx: The Visual Analysis of Measurements for the Assessment of Errors in Electrical Engines",
"doi": null,
"abstractUrl": "/magazine/cg/2022/02/09723551/1BocMIGbMD6",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/big-data/2022/8045/0/10020869",
"title": "Comparison of Teenagers’ Writing Using Word Clouds and Analyzing Engines",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2022/10020869/1KfR5ALNwEE",
"parentPublication": {
"id": "proceedings/big-data/2022/8045/0",
"title": "2022 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isspit/2019/5341/0/09001855",
"title": "Detecting Sarcastic and Complimentary Exclamations in English with Intonation patterns and Acoustic Features: A Case Study",
"doi": null,
"abstractUrl": "/proceedings-article/isspit/2019/09001855/1hHMiJl5fYQ",
"parentPublication": {
"id": "proceedings/isspit/2019/5341/0",
"title": "2019 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/mass/2021/4935/0/493500a633",
"title": "Pyrenote: a Web-based, Manual Annotation Tool for Passive Acoustic Monitoring",
"doi": null,
"abstractUrl": "/proceedings-article/mass/2021/493500a633/1ziOyp19B5e",
"parentPublication": {
"id": "proceedings/mass/2021/4935/0",
"title": "2021 IEEE 18th International Conference on Mobile Ad Hoc and Smart Systems (MASS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552242",
"articleId": "1xic4WSUlKE",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552195",
"articleId": "1xic0yNxnws",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBaoiK6h9u",
"name": "ttg202201-09552903s1-supp2-3114797.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552903s1-supp2-3114797.pdf",
"extension": "pdf",
"size": "4.93 MB",
"__typename": "WebExtraType"
},
{
"id": "1zBaosgekzC",
"name": "ttg202201-09552903s1-supp1-3114797.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552903s1-supp1-3114797.mp4",
"extension": "mp4",
"size": "47.3 MB",
"__typename": "WebExtraType"
},
{
"id": "1zBaonKlQk0",
"name": "ttg202201-09552903s1-supp3-3114797.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552903s1-supp3-3114797.pdf",
"extension": "pdf",
"size": "293 kB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xic0yNxnws",
"doi": "10.1109/TVCG.2021.3114844",
"abstract": "We explore how the lens of fictional superpowers can help characterize how visualizations empower people and provide inspiration for new visualization systems. Researchers and practitioners often tout visualizations' ability to “make the invisible visible” and to “enhance cognitive abilities.” Meanwhile superhero comics and other modern fiction often depict characters with similarly fantastic abilities that allow them to see and interpret the world in ways that transcend traditional human perception. We investigate the intersection of these domains, and show how the language of superpowers can be used to characterize existing visualization systems and suggest opportunities for new and empowering ones. We introduce two frameworks: The first characterizes seven underlying mechanisms that form the basis for a variety of visual superpowers portrayed in fiction. The second identifies seven ways in which visualization tools and interfaces can instill a sense of empowerment in the people who use them. Building on these observations, we illustrate a diverse set of “visualization superpowers” and highlight opportunities for the visualization community to create new systems and interactions that empower new experiences with data Material and illustrations are available under CC-BY 4.0 at osf.io/8yhfz.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We explore how the lens of fictional superpowers can help characterize how visualizations empower people and provide inspiration for new visualization systems. Researchers and practitioners often tout visualizations' ability to “make the invisible visible” and to “enhance cognitive abilities.” Meanwhile superhero comics and other modern fiction often depict characters with similarly fantastic abilities that allow them to see and interpret the world in ways that transcend traditional human perception. We investigate the intersection of these domains, and show how the language of superpowers can be used to characterize existing visualization systems and suggest opportunities for new and empowering ones. We introduce two frameworks: The first characterizes seven underlying mechanisms that form the basis for a variety of visual superpowers portrayed in fiction. The second identifies seven ways in which visualization tools and interfaces can instill a sense of empowerment in the people who use them. Building on these observations, we illustrate a diverse set of “visualization superpowers” and highlight opportunities for the visualization community to create new systems and interactions that empower new experiences with data Material and illustrations are available under CC-BY 4.0 at osf.io/8yhfz.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We explore how the lens of fictional superpowers can help characterize how visualizations empower people and provide inspiration for new visualization systems. Researchers and practitioners often tout visualizations' ability to “make the invisible visible” and to “enhance cognitive abilities.” Meanwhile superhero comics and other modern fiction often depict characters with similarly fantastic abilities that allow them to see and interpret the world in ways that transcend traditional human perception. We investigate the intersection of these domains, and show how the language of superpowers can be used to characterize existing visualization systems and suggest opportunities for new and empowering ones. We introduce two frameworks: The first characterizes seven underlying mechanisms that form the basis for a variety of visual superpowers portrayed in fiction. The second identifies seven ways in which visualization tools and interfaces can instill a sense of empowerment in the people who use them. Building on these observations, we illustrate a diverse set of “visualization superpowers” and highlight opportunities for the visualization community to create new systems and interactions that empower new experiences with data Material and illustrations are available under CC-BY 4.0 at osf.io/8yhfz.",
"title": "Perception! Immersion! Empowerment! Superpowers as Inspiration for Visualization",
"normalizedTitle": "Perception! Immersion! Empowerment! Superpowers as Inspiration for Visualization",
"fno": "09552195",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Data Visualization",
"Visualization",
"Cognition",
"Interactive Systems",
"Tools",
"Pragmatics",
"Pattern Recognition",
"Visualization",
"Superpowers",
"Empowerment",
"Vision",
"Perception",
"Cognition",
"Fiction",
"Situated Visualization"
],
"authors": [
{
"givenName": "Wesley",
"surname": "Willett",
"fullName": "Wesley Willett",
"affiliation": "University of Calgary, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Bon Adriel",
"surname": "Aseniero",
"fullName": "Bon Adriel Aseniero",
"affiliation": "Autodesk, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Sheelagh",
"surname": "Carpendale",
"fullName": "Sheelagh Carpendale",
"affiliation": "Simon Fraser Univ., Canada",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Pierre",
"surname": "Dragicevic",
"fullName": "Pierre Dragicevic",
"affiliation": "Universite Paris-Saclay, CNRS. Inria. LISN, France",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yvonne",
"surname": "Jansen",
"fullName": "Yvonne Jansen",
"affiliation": "Sorbonne Universite, CNRS, ISIR, France",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Lora",
"surname": "Oehlberg",
"fullName": "Lora Oehlberg",
"affiliation": "University of Calgary, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Petra",
"surname": "Isenberg",
"fullName": "Petra Isenberg",
"affiliation": "Universite Paris-Saclay, CNRS. Inria. LISN, France",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "22-32",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/icds/2010/3953/0/3953a285",
"title": "Visualizing Plot in 3D",
"doi": null,
"abstractUrl": "/proceedings-article/icds/2010/3953a285/12OmNqG0SL8",
"parentPublication": {
"id": "proceedings/icds/2010/3953/0",
"title": "International Conference on the Digital Society",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2009/3733/0/3733a003",
"title": "Visual Perception of Parallel Coordinate Visualizations",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2009/3733a003/12OmNwGZNMM",
"parentPublication": {
"id": "proceedings/iv/2009/3733/0",
"title": "2009 13th International Conference Information Visualisation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/lab-rs/2008/3272/0/3272a077",
"title": "Using Cognitive Semantics to Integrate Perception and Motion in a Behavior-Based Robot",
"doi": null,
"abstractUrl": "/proceedings-article/lab-rs/2008/3272a077/12OmNx3q6WW",
"parentPublication": {
"id": "proceedings/lab-rs/2008/3272/0",
"title": "Learning and Adaptive Behaviors for Robotic Systems, ECSIS Symposium on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2004/2177/0/21770519",
"title": "Learning from Architects: The Difference between Knowledge Visualization and Information Visualization",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2004/21770519/12OmNx9nGLN",
"parentPublication": {
"id": "proceedings/iv/2004/2177/0",
"title": "Proceedings. Eighth International Conference on Information Visualisation, 2004. IV 2004.",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ozchi/1998/9206/0/92060200",
"title": "Integrating Metric Visualization into a Commercial User-Interface Builder",
"doi": null,
"abstractUrl": "/proceedings-article/ozchi/1998/92060200/12OmNyuPLbI",
"parentPublication": {
"id": "proceedings/ozchi/1998/9206/0",
"title": "Computer-Human Interaction, Australasian Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09904456",
"title": "Measuring Effects of Spatial Visualization and Domain on Visualization Task Performance: A Comparative Study",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09904456/1H1gmktPnLa",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2020/01/08836087",
"title": "The Impact of Immersion on Cluster Identification Tasks",
"doi": null,
"abstractUrl": "/journal/tg/2020/01/08836087/1dia1nodZeM",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2020/5608/0/09089446",
"title": "Graphical Perception for Immersive Analytics",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2020/09089446/1jIxfA3tlUk",
"parentPublication": {
"id": "proceedings/vr/2020/5608/0",
"title": "2020 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/12/09492011",
"title": "A Survey of Perception-Based Visualization Studies by Task",
"doi": null,
"abstractUrl": "/journal/tg/2022/12/09492011/1volPuHGMdW",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/01/09572234",
"title": "Professional Differences: A Comparative Study of Visualization Task Performance and Spatial Ability Across Disciplines",
"doi": null,
"abstractUrl": "/journal/tg/2022/01/09572234/1xH5FXdMnoA",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552903",
"articleId": "1xibWJujrkk",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552927",
"articleId": "1xic6oeRxnO",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xic6oeRxnO",
"doi": "10.1109/TVCG.2021.3114808",
"abstract": "3D asymmetric tensor fields have found many applications in science and engineering domains, such as fluid dynamics and solid mechanics. 3D asymmetric tensors can have complex eigenvalues, which makes their analysis and visualization more challenging than 3D symmetric tensors. Existing research in tensor field visualization focuses on 2D asymmetric tensor fields and 3D symmetric tensor fields. In this paper, we address the analysis and visualization of 3D asymmetric tensor fields. We introduce six topological surfaces and one topological curve, which lead to an eigenvalue space based on the tensor mode that we define. In addition, we identify several non-topological feature surfaces that are nonetheless physically important. Included in our analysis are the realizations that triple degenerate tensors are structurally stable and form curves, unlike the case for 3D symmetric tensors fields. Furthermore, there are two different ways of measuring the relative strengths of rotation and angular deformation in the tensor fields, unlike the case for 2D asymmetric tensor fields. We extract these feature surfaces using the A-patches algorithm. However, since three of our feature surfaces are quadratic, we develop a method to extract quadratic surfaces at any given accuracy. To facilitate the analysis of eigenvector fields, we visualize a hyperstreamline as a tree stem with the other two eigenvectors represented as thorns in the real domain or the dual-eigenvectors as leaves in the complex domain. To demonstrate the effectiveness of our analysis and visualization, we apply our approach to datasets from solid mechanics and fluid dynamics.",
"abstracts": [
{
"abstractType": "Regular",
"content": "3D asymmetric tensor fields have found many applications in science and engineering domains, such as fluid dynamics and solid mechanics. 3D asymmetric tensors can have complex eigenvalues, which makes their analysis and visualization more challenging than 3D symmetric tensors. Existing research in tensor field visualization focuses on 2D asymmetric tensor fields and 3D symmetric tensor fields. In this paper, we address the analysis and visualization of 3D asymmetric tensor fields. We introduce six topological surfaces and one topological curve, which lead to an eigenvalue space based on the tensor mode that we define. In addition, we identify several non-topological feature surfaces that are nonetheless physically important. Included in our analysis are the realizations that triple degenerate tensors are structurally stable and form curves, unlike the case for 3D symmetric tensors fields. Furthermore, there are two different ways of measuring the relative strengths of rotation and angular deformation in the tensor fields, unlike the case for 2D asymmetric tensor fields. We extract these feature surfaces using the A-patches algorithm. However, since three of our feature surfaces are quadratic, we develop a method to extract quadratic surfaces at any given accuracy. To facilitate the analysis of eigenvector fields, we visualize a hyperstreamline as a tree stem with the other two eigenvectors represented as thorns in the real domain or the dual-eigenvectors as leaves in the complex domain. To demonstrate the effectiveness of our analysis and visualization, we apply our approach to datasets from solid mechanics and fluid dynamics.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "3D asymmetric tensor fields have found many applications in science and engineering domains, such as fluid dynamics and solid mechanics. 3D asymmetric tensors can have complex eigenvalues, which makes their analysis and visualization more challenging than 3D symmetric tensors. Existing research in tensor field visualization focuses on 2D asymmetric tensor fields and 3D symmetric tensor fields. In this paper, we address the analysis and visualization of 3D asymmetric tensor fields. We introduce six topological surfaces and one topological curve, which lead to an eigenvalue space based on the tensor mode that we define. In addition, we identify several non-topological feature surfaces that are nonetheless physically important. Included in our analysis are the realizations that triple degenerate tensors are structurally stable and form curves, unlike the case for 3D symmetric tensors fields. Furthermore, there are two different ways of measuring the relative strengths of rotation and angular deformation in the tensor fields, unlike the case for 2D asymmetric tensor fields. We extract these feature surfaces using the A-patches algorithm. However, since three of our feature surfaces are quadratic, we develop a method to extract quadratic surfaces at any given accuracy. To facilitate the analysis of eigenvector fields, we visualize a hyperstreamline as a tree stem with the other two eigenvectors represented as thorns in the real domain or the dual-eigenvectors as leaves in the complex domain. To demonstrate the effectiveness of our analysis and visualization, we apply our approach to datasets from solid mechanics and fluid dynamics.",
"title": "Feature Curves and Surfaces of 3D Asymmetric Tensor Fields",
"normalizedTitle": "Feature Curves and Surfaces of 3D Asymmetric Tensor Fields",
"fno": "09552927",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Data Visualisation",
"Eigenvalues And Eigenfunctions",
"Tensors",
"Topology",
"3 D Asymmetric Tensor Fields",
"3 D Asymmetric Tensors",
"Tensor Field Visualization",
"3 D Symmetric Tensor Fields",
"Tensor Mode",
"Nontopological Feature Surfaces",
"Triple Degenerate Tensors",
"3 D Symmetric Tensors Fields",
"Tensors",
"Eigenvalues And Eigenfunctions",
"Three Dimensional Displays",
"Visualization",
"Feature Extraction",
"Solids",
"Topology",
"Tensor Field Visualization",
"3 D Asymmetric Tensor Fields",
"Tensor Field Topology",
"Traceless Tensors",
"Feature Surface Extraction",
"Degenerate Surfaces",
"Neutral Surfaces",
"Balanced Surfaces",
"Triple Degenerate Curves"
],
"authors": [
{
"givenName": "Shih-Hsuan",
"surname": "Hung",
"fullName": "Shih-Hsuan Hung",
"affiliation": "School of Electrical Engineering and Computer Science, Oregon State University, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yue",
"surname": "Zhang",
"fullName": "Yue Zhang",
"affiliation": "School of Electrical Engineering and Computer Science, Oregon State University, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Harry",
"surname": "Yeh",
"fullName": "Harry Yeh",
"affiliation": "School of Civil and Construction Engineering, Oregon State University, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Eugene",
"surname": "Zhang",
"fullName": "Eugene Zhang",
"affiliation": "School of Electrical Engineering and Computer Science, Oregon State University, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "33-42",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/ieee-vis/2005/2766/0/27660001",
"title": "2D Asymmetric Tensor Analysis",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-vis/2005/27660001/12OmNAY79q0",
"parentPublication": {
"id": "proceedings/ieee-vis/2005/2766/0",
"title": "Visualization Conference, IEEE",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ieee-vis/2004/8788/0/87880313",
"title": "Topological Lines in 3D Tensor Fields",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-vis/2004/87880313/12OmNApLGKA",
"parentPublication": {
"id": "proceedings/ieee-vis/2004/8788/0",
"title": "Visualization Conference, IEEE",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ieee-vis/2005/2766/0/01532770",
"title": "2D asymmetric tensor analysis",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-vis/2005/01532770/12OmNCw3z9K",
"parentPublication": {
"id": "proceedings/ieee-vis/2005/2766/0",
"title": "Visualization Conference, IEEE",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/visual/1994/6627/0/00346326",
"title": "The topology of symmetric, second-order tensor fields",
"doi": null,
"abstractUrl": "/proceedings-article/visual/1994/00346326/12OmNvxKu1Q",
"parentPublication": {
"id": "proceedings/visual/1994/6627/0",
"title": "Proceedings Visualization '94",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ieee-vis/2005/2766/0/01532841",
"title": "Topological structures of 3D tensor fields",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-vis/2005/01532841/12OmNx5GTXp",
"parentPublication": {
"id": "proceedings/ieee-vis/2005/2766/0",
"title": "Visualization Conference, IEEE",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ieee-vis/2005/2766/0/27660070",
"title": "Topological Structures of 3D Tensor Fields",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-vis/2005/27660070/12OmNxeusY2",
"parentPublication": {
"id": "proceedings/ieee-vis/2005/2766/0",
"title": "Visualization Conference, IEEE",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2016/03/07286850",
"title": "Feature Surfaces in Symmetric Tensor Fields Based on Eigenvalue Manifold",
"doi": null,
"abstractUrl": "/journal/tg/2016/03/07286850/13rRUwhpBE8",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/01/08453873",
"title": "Robust and Fast Extraction of 3D Symmetric Tensor Field Topology",
"doi": null,
"abstractUrl": "/journal/tg/2019/01/08453873/17D45WHONif",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2020/01/08805436",
"title": "Multi-Scale Topological Analysis of Asymmetric Tensor Fields on Surfaces",
"doi": null,
"abstractUrl": "/journal/tg/2020/01/08805436/1cG4IGNd2Y8",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/02/09224154",
"title": "Mode Surfaces of Symmetric Tensor Fields: Topological Analysis and Seamless Extraction",
"doi": null,
"abstractUrl": "/journal/tg/2021/02/09224154/1nV63QG11le",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552195",
"articleId": "1xic0yNxnws",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09555491",
"articleId": "1xjQX1LHQJi",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBaTxP3Sms",
"name": "ttg202201-09552927s1-supp1-3114808.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552927s1-supp1-3114808.mp4",
"extension": "mp4",
"size": "122 MB",
"__typename": "WebExtraType"
},
{
"id": "1zBaTjMcxiw",
"name": "ttg202201-09552927s1-supp2-3114808.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552927s1-supp2-3114808.pdf",
"extension": "pdf",
"size": "14.2 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xjQX1LHQJi",
"doi": "10.1109/TVCG.2021.3114860",
"abstract": "Visual information displays are typically composed of multiple visualizations that are used to facilitate an understanding of the underlying data. A common example are dashboards, which are frequently used in domains such as finance, process monitoring and business intelligence. However, users may not be aware of existing guidelines and lack expert design knowledge when composing such multi-view visualizations. In this paper, we present semantic snapping, an approach to help non-expert users design effective multi-view visualizations from sets of pre-existing views. When a particular view is placed on a canvas, it is “aligned” with the remaining views-not with respect to its geometric layout, but based on aspects of the visual encoding itself, such as how data dimensions are mapped to channels. Our method uses an on-the-fly procedure to detect and suggest resolutions for conflicting, misleading, or ambiguous designs, as well as to provide suggestions for alternative presentations. With this approach, users can be guided to avoid common pitfalls encountered when composing visualizations. Our provided examples and case studies demonstrate the usefulness and validity of our approach.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Visual information displays are typically composed of multiple visualizations that are used to facilitate an understanding of the underlying data. A common example are dashboards, which are frequently used in domains such as finance, process monitoring and business intelligence. However, users may not be aware of existing guidelines and lack expert design knowledge when composing such multi-view visualizations. In this paper, we present semantic snapping, an approach to help non-expert users design effective multi-view visualizations from sets of pre-existing views. When a particular view is placed on a canvas, it is “aligned” with the remaining views-not with respect to its geometric layout, but based on aspects of the visual encoding itself, such as how data dimensions are mapped to channels. Our method uses an on-the-fly procedure to detect and suggest resolutions for conflicting, misleading, or ambiguous designs, as well as to provide suggestions for alternative presentations. With this approach, users can be guided to avoid common pitfalls encountered when composing visualizations. Our provided examples and case studies demonstrate the usefulness and validity of our approach.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Visual information displays are typically composed of multiple visualizations that are used to facilitate an understanding of the underlying data. A common example are dashboards, which are frequently used in domains such as finance, process monitoring and business intelligence. However, users may not be aware of existing guidelines and lack expert design knowledge when composing such multi-view visualizations. In this paper, we present semantic snapping, an approach to help non-expert users design effective multi-view visualizations from sets of pre-existing views. When a particular view is placed on a canvas, it is “aligned” with the remaining views-not with respect to its geometric layout, but based on aspects of the visual encoding itself, such as how data dimensions are mapped to channels. Our method uses an on-the-fly procedure to detect and suggest resolutions for conflicting, misleading, or ambiguous designs, as well as to provide suggestions for alternative presentations. With this approach, users can be guided to avoid common pitfalls encountered when composing visualizations. Our provided examples and case studies demonstrate the usefulness and validity of our approach.",
"title": "Semantic Snapping for Guided Multi-View Visualization Design",
"normalizedTitle": "Semantic Snapping for Guided Multi-View Visualization Design",
"fno": "09555491",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Data Visualization",
"Semantics",
"Task Analysis",
"Guidelines",
"Visualization",
"Tools",
"Image Color Analysis",
"Tabular Data",
"Guidelines",
"Mixed Initiative Human Machine Analysis",
"Coordinated And Multiple Views"
],
"authors": [
{
"givenName": "Yngve S.",
"surname": "Kristiansen",
"fullName": "Yngve S. Kristiansen",
"affiliation": "Department of Informatics, University of Bergen, Norway",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Laura",
"surname": "Garrison",
"fullName": "Laura Garrison",
"affiliation": "Department of Informatics, University of Bergen, Norway",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Stefan",
"surname": "Bruckner",
"fullName": "Stefan Bruckner",
"affiliation": "Department of Informatics, University of Bergen, Norway",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "43-53",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/vizsec/2017/2693/0/08062195",
"title": "Expert-interviews led analysis of EEVi — A model for effective visualization in cyber-security",
"doi": null,
"abstractUrl": "/proceedings-article/vizsec/2017/08062195/12OmNyfdOR3",
"parentPublication": {
"id": "proceedings/vizsec/2017/2693/0",
"title": "2017 IEEE Symposium on Visualization for Cyber Security (VizSec)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2013/2840/0/2840a649",
"title": "Tracking via Robust Multi-task Multi-view Joint Sparse Representation",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2013/2840a649/12OmNzR8CzP",
"parentPublication": {
"id": "proceedings/iccv/2013/2840/0",
"title": "2013 IEEE International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdm/2014/4302/0/4302a590",
"title": "Multi-graph-view Learning for Graph Classification",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2014/4302a590/12OmNzkuKJl",
"parentPublication": {
"id": "proceedings/icdm/2014/4302/0",
"title": "2014 IEEE International Conference on Data Mining (ICDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2018/01/08017651",
"title": "Keeping Multiple Views Consistent: Constraints, Validations, and Exceptions in Visualization Authoring",
"doi": null,
"abstractUrl": "/journal/tg/2018/01/08017651/13rRUNvyaf7",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2009/06/ttg2009061383",
"title": "Interactive Coordinated Multiple-View Visualization of Biomechanical Motion Data",
"doi": null,
"abstractUrl": "/journal/tg/2009/06/ttg2009061383/13rRUwfI0Q3",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09903511",
"title": "Supporting Expressive and Faithful Pictorial Visualization Design with Visual Style Transfer",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09903511/1GZokWw73mo",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/10029921",
"title": "Semi-Automatic Layout Adaptation for Responsive Multiple-View Visualization Design",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/10029921/1KmyX4gJuMg",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2020/01/08805429",
"title": "Color Crafting: Automating the Construction of Designer Quality Color Ramps",
"doi": null,
"abstractUrl": "/journal/tg/2020/01/08805429/1cG4w5XPNUQ",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar-adjunct/2019/4765/0/476500a372",
"title": "Visualization-Guided Attention Direction in Dynamic Control Tasks",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2019/476500a372/1gysnIklSSY",
"parentPublication": {
"id": "proceedings/ismar-adjunct/2019/4765/0",
"title": "2019 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/09/09035622",
"title": "LADV: Deep Learning Assisted Authoring of Dashboard Visualizations From Images and Sketches",
"doi": null,
"abstractUrl": "/journal/tg/2021/09/09035622/1iaeAO11H6o",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552927",
"articleId": "1xic6oeRxnO",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09555226",
"articleId": "1xjQVmm2wE0",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBaCtLPJ8A",
"name": "ttg202201-09555491s1-supp1-3114860.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09555491s1-supp1-3114860.mp4",
"extension": "mp4",
"size": "52.6 MB",
"__typename": "WebExtraType"
},
{
"id": "1zBaCPh5D5C",
"name": "ttg202201-09555491s1-supp2-3114860.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09555491s1-supp2-3114860.pdf",
"extension": "pdf",
"size": "1.54 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xjQVmm2wE0",
"doi": "10.1109/TVCG.2021.3114801",
"abstract": "Multiple-view visualization (MV) has been heavily used in visual analysis tools for sensemaking of data in various domains (e.g., bioinformatics, cybersecurity and text analytics). One common task of visual analysis with multiple views is to relate data across different views. For example, to identify threats, an intelligence analyst needs to link people from a social network graph with locations on a crime-map, and then search for and read relevant documents. Currently, exploring cross-view data relationships heavily relies on view-coordination techniques (e.g., brushing and linking), which may require significant user effort on many trial-and-error attempts, such as repetitiously selecting elements in one view, and then observing and following elements highlighted in other views. To address this, we present SightBi, a visual analytics approach for supporting cross-view data relationship explorations. We discuss the design rationale of SightBi in detail, with identified user tasks regarding the use of cross-view data relationships. SightBi formalizes cross-view data relationships as biclusters, computes them from a dataset, and uses a bi-context design that highlights creating stand-alone relationship-views. This helps preserve existing views and offers an overview of cross-view data relationships to guide user exploration. Moreover, SightBi allows users to interactively manage the layout of multiple views by using newly created relationship-views. With a usage scenario, we demonstrate the usefulness of SightBi for sensemaking of cross-view data relationships.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Multiple-view visualization (MV) has been heavily used in visual analysis tools for sensemaking of data in various domains (e.g., bioinformatics, cybersecurity and text analytics). One common task of visual analysis with multiple views is to relate data across different views. For example, to identify threats, an intelligence analyst needs to link people from a social network graph with locations on a crime-map, and then search for and read relevant documents. Currently, exploring cross-view data relationships heavily relies on view-coordination techniques (e.g., brushing and linking), which may require significant user effort on many trial-and-error attempts, such as repetitiously selecting elements in one view, and then observing and following elements highlighted in other views. To address this, we present SightBi, a visual analytics approach for supporting cross-view data relationship explorations. We discuss the design rationale of SightBi in detail, with identified user tasks regarding the use of cross-view data relationships. SightBi formalizes cross-view data relationships as biclusters, computes them from a dataset, and uses a bi-context design that highlights creating stand-alone relationship-views. This helps preserve existing views and offers an overview of cross-view data relationships to guide user exploration. Moreover, SightBi allows users to interactively manage the layout of multiple views by using newly created relationship-views. With a usage scenario, we demonstrate the usefulness of SightBi for sensemaking of cross-view data relationships.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Multiple-view visualization (MV) has been heavily used in visual analysis tools for sensemaking of data in various domains (e.g., bioinformatics, cybersecurity and text analytics). One common task of visual analysis with multiple views is to relate data across different views. For example, to identify threats, an intelligence analyst needs to link people from a social network graph with locations on a crime-map, and then search for and read relevant documents. Currently, exploring cross-view data relationships heavily relies on view-coordination techniques (e.g., brushing and linking), which may require significant user effort on many trial-and-error attempts, such as repetitiously selecting elements in one view, and then observing and following elements highlighted in other views. To address this, we present SightBi, a visual analytics approach for supporting cross-view data relationship explorations. We discuss the design rationale of SightBi in detail, with identified user tasks regarding the use of cross-view data relationships. SightBi formalizes cross-view data relationships as biclusters, computes them from a dataset, and uses a bi-context design that highlights creating stand-alone relationship-views. This helps preserve existing views and offers an overview of cross-view data relationships to guide user exploration. Moreover, SightBi allows users to interactively manage the layout of multiple views by using newly created relationship-views. With a usage scenario, we demonstrate the usefulness of SightBi for sensemaking of cross-view data relationships.",
"title": "SightBi: Exploring Cross-View Data Relationships with Biclusters",
"normalizedTitle": "SightBi: Exploring Cross-View Data Relationships with Biclusters",
"fno": "09555226",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Visualization",
"Data Visualization",
"Tools",
"Task Analysis",
"Layout",
"Sun",
"Bioinformatics",
"Cross View Data Relationship",
"Multi View Visualization",
"Bicluster",
"Visual Analytics"
],
"authors": [
{
"givenName": "Maoyuan",
"surname": "Sun",
"fullName": "Maoyuan Sun",
"affiliation": "Northern Illinois University, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Abdul Rahman",
"surname": "Shaikh",
"fullName": "Abdul Rahman Shaikh",
"affiliation": "Northern Illinois University, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Hamed",
"surname": "Alhoori",
"fullName": "Hamed Alhoori",
"affiliation": "Northern Illinois University, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jian",
"surname": "Zhao",
"fullName": "Jian Zhao",
"affiliation": "University of Waterloo, Canada",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "54-64",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/cvpr/2016/8851/0/8851e847",
"title": "Multi-view Deep Network for Cross-View Classification",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2016/8851e847/12OmNBpmDC1",
"parentPublication": {
"id": "proceedings/cvpr/2016/8851/0",
"title": "2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2014/11/06778788",
"title": "Mining Semantically Consistent Patterns for Cross-View Data",
"doi": null,
"abstractUrl": "/journal/tk/2014/11/06778788/13rRUNvgz4R",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2016/01/07192715",
"title": "BiSet: Semantic Edge Bundling with Biclusters for Sensemaking",
"doi": null,
"abstractUrl": "/journal/tg/2016/01/07192715/13rRUNvgz9T",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2022/8563/0/09859981",
"title": "Decomposing Identity and View for Cross-View Gait Recognition",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2022/09859981/1G9EzfoOOe4",
"parentPublication": {
"id": "proceedings/icme/2022/8563/0",
"title": "2022 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vis/2019/4941/0/08933655",
"title": "Towards Quantifying Multiple View Layouts in Visualisation as Seen from Research Publications",
"doi": null,
"abstractUrl": "/proceedings-article/vis/2019/08933655/1fTgHP2omAM",
"parentPublication": {
"id": "proceedings/vis/2019/4941/0",
"title": "2019 IEEE Visualization Conference (VIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2019/4803/0/480300h504",
"title": "Learning Relationships for Multi-View 3D Object Recognition",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2019/480300h504/1hVldkkuBAA",
"parentPublication": {
"id": "proceedings/iccv/2019/4803/0",
"title": "2019 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2019/4803/0/480300i099",
"title": "Cross-View Policy Learning for Street Navigation",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2019/480300i099/1hVlzyJbr8I",
"parentPublication": {
"id": "proceedings/iccv/2019/4803/0",
"title": "2019 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2021/3864/0/09428184",
"title": "Cross-View Equivariant Auto-Encoder",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2021/09428184/1uilQ2tED6w",
"parentPublication": {
"id": "proceedings/icme/2021/3864/0",
"title": "2021 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/12/09508898",
"title": "Towards Systematic Design Considerations for Visualizing Cross-View Data Relationships",
"doi": null,
"abstractUrl": "/journal/tg/2022/12/09508898/1vQzkzRdSWk",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2021/4509/0/450900a557",
"title": "Cross-View Cross-Scene Multi-View Crowd Counting",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2021/450900a557/1yeKfeZSsXC",
"parentPublication": {
"id": "proceedings/cvpr/2021/4509/0",
"title": "2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09555491",
"articleId": "1xjQX1LHQJi",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552892",
"articleId": "1xibYYzLaWk",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBazFNIbv2",
"name": "ttg202201-09555226s1-supp1-3114801.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09555226s1-supp1-3114801.mp4",
"extension": "mp4",
"size": "8.17 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xibYYzLaWk",
"doi": "10.1109/TVCG.2021.3114812",
"abstract": "Lithium ion batteries (LIBs) are widely used as important energy sources for mobile phones, electric vehicles, and drones. Experts have attempted to replace liquid electrolytes with solid electrolytes that have wider electrochemical window and higher stability due to the potential safety risks, such as electrolyte leakage, flammable solvents, poor thermal stability, and many side reactions caused by liquid electrolytes. However, finding suitable alternative materials using traditional approaches is very difficult due to the incredibly high cost in searching. Machine learning (ML)-based methods are currently introduced and used for material prediction. However, learning tools designed for domain experts to conduct intuitive performance comparison and analysis of ML models are rare. In this case, we propose an interactive visualization system for experts to select suitable ML models and understand and explore the predication results comprehensively. Our system uses a multifaceted visualization scheme designed to support analysis from various perspectives, such as feature distribution, data similarity, model performance, and result presentation. Case studies with actual lab experiments have been conducted by the experts, and the final results confirmed the effectiveness and helpfulness of our system.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Lithium ion batteries (LIBs) are widely used as important energy sources for mobile phones, electric vehicles, and drones. Experts have attempted to replace liquid electrolytes with solid electrolytes that have wider electrochemical window and higher stability due to the potential safety risks, such as electrolyte leakage, flammable solvents, poor thermal stability, and many side reactions caused by liquid electrolytes. However, finding suitable alternative materials using traditional approaches is very difficult due to the incredibly high cost in searching. Machine learning (ML)-based methods are currently introduced and used for material prediction. However, learning tools designed for domain experts to conduct intuitive performance comparison and analysis of ML models are rare. In this case, we propose an interactive visualization system for experts to select suitable ML models and understand and explore the predication results comprehensively. Our system uses a multifaceted visualization scheme designed to support analysis from various perspectives, such as feature distribution, data similarity, model performance, and result presentation. Case studies with actual lab experiments have been conducted by the experts, and the final results confirmed the effectiveness and helpfulness of our system.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Lithium ion batteries (LIBs) are widely used as important energy sources for mobile phones, electric vehicles, and drones. Experts have attempted to replace liquid electrolytes with solid electrolytes that have wider electrochemical window and higher stability due to the potential safety risks, such as electrolyte leakage, flammable solvents, poor thermal stability, and many side reactions caused by liquid electrolytes. However, finding suitable alternative materials using traditional approaches is very difficult due to the incredibly high cost in searching. Machine learning (ML)-based methods are currently introduced and used for material prediction. However, learning tools designed for domain experts to conduct intuitive performance comparison and analysis of ML models are rare. In this case, we propose an interactive visualization system for experts to select suitable ML models and understand and explore the predication results comprehensively. Our system uses a multifaceted visualization scheme designed to support analysis from various perspectives, such as feature distribution, data similarity, model performance, and result presentation. Case studies with actual lab experiments have been conducted by the experts, and the final results confirmed the effectiveness and helpfulness of our system.",
"title": "matExplorer: Visual Exploration on Predicting Ionic Conductivity for Solid-state Electrolytes",
"normalizedTitle": "matExplorer: Visual Exploration on Predicting Ionic Conductivity for Solid-state Electrolytes",
"fno": "09552892",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Data Visualisation",
"Electrochemical Electrodes",
"Electrolytes",
"Ionic Conductivity",
"Learning Artificial Intelligence",
"Lithium Compounds",
"Polymer Electrolytes",
"Secondary Cells",
"Solid Electrolytes",
"Thermal Stability",
"Visual Exploration",
"Predicting Ionic Conductivity",
"Solid State Electrolytes",
"Lithium Ion Batteries",
"Important Energy Sources",
"Mobile Phones",
"Electric Vehicles",
"Liquid Electrolytes",
"Solid Electrolytes",
"Wider Electrochemical Window",
"Potential Safety Risks",
"Electrolyte Leakage",
"Flammable Solvents",
"Poor Thermal Stability",
"Suitable Alternative Materials",
"Incredibly High Cost",
"Machine Learning Based Methods",
"Material Prediction",
"Learning Tools",
"Domain Experts",
"Intuitive Performance Comparison",
"Interactive Visualization System",
"Suitable ML Models",
"Multifaceted Visualization Scheme",
"Electrolytes",
"Solids",
"Liquids",
"Conductivity",
"Batteries",
"Lithium",
"Thermal Stability",
"Interactive Visualization",
"Machine Learning",
"Materials Discovery",
"Ionic Conductivity",
"High Dimensional Data",
"Solid State Electrolytes"
],
"authors": [
{
"givenName": "Jiansu",
"surname": "Pu",
"fullName": "Jiansu Pu",
"affiliation": "VisBig Lab, School of Computer Science and Engineering, University of Electronic Science and Technology, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Hui",
"surname": "Shao",
"fullName": "Hui Shao",
"affiliation": "VisBig Lab, School of Computer Science and Engineering, University of Electronic Science and Technology, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Boyang",
"surname": "Gao",
"fullName": "Boyang Gao",
"affiliation": "VisBig Lab, School of Computer Science and Engineering, University of Electronic Science and Technology, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Zhengguo",
"surname": "Zhu",
"fullName": "Zhengguo Zhu",
"affiliation": "VisBig Lab, School of Computer Science and Engineering, University of Electronic Science and Technology, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yanlin",
"surname": "Zhu",
"fullName": "Yanlin Zhu",
"affiliation": "Shenzhen Clean Energy Research Institute, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yunbo",
"surname": "Rao",
"fullName": "Yunbo Rao",
"affiliation": "VisBig Lab, School of Computer Science and Engineering, University of Electronic Science and Technology, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yong",
"surname": "Xiang",
"fullName": "Yong Xiang",
"affiliation": "VisBig Lab, School of Computer Science and Engineering, University of Electronic Science and Technology, China",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "65-75",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/isdea/2013/4893/0/06455228",
"title": "Thermal Conductivity Measurement about Fluid and Solid",
"doi": null,
"abstractUrl": "/proceedings-article/isdea/2013/06455228/12OmNApcuwI",
"parentPublication": {
"id": "proceedings/isdea/2013/4893/0",
"title": "2013 Third International Conference on Intelligent System Design and Engineering Applications (ISDEA 2013)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hpcmp-ugc/2009/3946/0/3946a175",
"title": "Design of Energetic Ionic Liquids",
"doi": null,
"abstractUrl": "/proceedings-article/hpcmp-ugc/2009/3946a175/12OmNBTawzL",
"parentPublication": {
"id": "proceedings/hpcmp-ugc/2009/3946/0",
"title": "HPCMP Users Group Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ecodim/2005/0081/0/01619373",
"title": "Grain-Size Dependence of Electrolytic Properties in 25 at.% Yttrium Doped Ceria Solid Electrolytes",
"doi": null,
"abstractUrl": "/proceedings-article/ecodim/2005/01619373/12OmNroijky",
"parentPublication": {
"id": "proceedings/ecodim/2005/0081/0",
"title": "Fourth International Symposium on Environmentally Conscious Design and Inverse Manufacturing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdl/2002/7350/0/01022682",
"title": "Motion at the liquid-solid interface-developing design tools from fundamental models",
"doi": null,
"abstractUrl": "/proceedings-article/icdl/2002/01022682/12OmNwDACC6",
"parentPublication": {
"id": "proceedings/icdl/2002/7350/0",
"title": "Proceedings of 14th International Conference on Dielectric Liquids",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdl/2002/7350/0/01022770",
"title": "Electrical properties of fluorinated gel electrolytes using conducting solution and its application to secondary battery",
"doi": null,
"abstractUrl": "/proceedings-article/icdl/2002/01022770/12OmNwxlrhj",
"parentPublication": {
"id": "proceedings/icdl/2002/7350/0",
"title": "Proceedings of 14th International Conference on Dielectric Liquids",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdl/2002/7350/0/01022745",
"title": "Surface conductivity in liquid-solid interface due to image force",
"doi": null,
"abstractUrl": "/proceedings-article/icdl/2002/01022745/12OmNxzMnWM",
"parentPublication": {
"id": "proceedings/icdl/2002/7350/0",
"title": "Proceedings of 14th International Conference on Dielectric Liquids",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdl/2002/7350/0/01022731",
"title": "Influence of hydrostatic pressure on the characteristics of discharges propagating on solid/liquid insulating interfaces under AC and DC voltages",
"doi": null,
"abstractUrl": "/proceedings-article/icdl/2002/01022731/12OmNyp9Mgu",
"parentPublication": {
"id": "proceedings/icdl/2002/7350/0",
"title": "Proceedings of 14th International Conference on Dielectric Liquids",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icics/2018/6483/0/648300a201",
"title": "Conductivity Enhancement of PEMA Based Plasticized Polymer Electrolyte Using Cadmium Sulphide Nanofillers",
"doi": null,
"abstractUrl": "/proceedings-article/icics/2018/648300a201/17D45WgziQP",
"parentPublication": {
"id": "proceedings/icics/2018/6483/0",
"title": "2018 International Conference on Intelligent Circuits and Systems (ICICS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmcce/2019/4689/0/468900a138",
"title": "Study on the Role of Solid Surface on Nanochannel Flow with Molecular Dynamics Simulation",
"doi": null,
"abstractUrl": "/proceedings-article/icmcce/2019/468900a138/1h0Fjt7kZna",
"parentPublication": {
"id": "proceedings/icmcce/2019/4689/0",
"title": "2019 4th International Conference on Mechanical, Control and Computer Engineering (ICMCCE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pacificvis/2021/3931/0/393100a001",
"title": "Visual Analysis on Machine Learning Assisted Prediction of Ionic Conductivity for Solid-State Electrolytes",
"doi": null,
"abstractUrl": "/proceedings-article/pacificvis/2021/393100a001/1tTtpOLXIrK",
"parentPublication": {
"id": "proceedings/pacificvis/2021/3931/0",
"title": "2021 IEEE 14th Pacific Visualization Symposium (PacificVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09555226",
"articleId": "1xjQVmm2wE0",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09645370",
"articleId": "1zc6D7Qkucw",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1zc6D7Qkucw",
"doi": "10.1109/TVCG.2021.3114819",
"abstract": "In the study of packed granular materials, the performance of a sample (e.g., the detonation of a high-energy explosive) often correlates to measurements of a fluid flowing through it. The “effective surface area,” the surface area accessible to the airflow, is typically measured using a permeametry apparatus that relates the flow conductance to the permeable surface area via the Carman-Kozeny equation. This equation allows calculating the flow rate of a fluid flowing through the granules packed in the sample for a given pressure drop. However, Carman-Kozeny makes inherent assumptions about tunnel shapes and flow paths that may not accurately hold in situations where the particles possess a wide distribution in shapes, sizes, and aspect ratios, as is true with many powdered systems of technological and commercial interest. To address this challenge, we replicate these measurements virtually on micro-CT images of the powdered material, introducing a new Pore Network Model based on the skeleton of the Morse-Smale complex. Pores are identified as basins of the complex, their incidence encodes adjacency, and the conductivity of the capillary between them is computed from the cross-section at their interface. We build and solve a resistive network to compute an approximate laminar fluid flow through the pore structure. We provide two means of estimating flow-permeable surface area: (i) by direct computation of conductivity, and (ii) by identifying dead-ends in the flow coupled with isosurface extraction and the application of the Carman-Kozeny equation, with the aim of establishing consistency over a range of particle shapes, sizes, porosity levels, and void distribution patterns.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In the study of packed granular materials, the performance of a sample (e.g., the detonation of a high-energy explosive) often correlates to measurements of a fluid flowing through it. The “effective surface area,” the surface area accessible to the airflow, is typically measured using a permeametry apparatus that relates the flow conductance to the permeable surface area via the Carman-Kozeny equation. This equation allows calculating the flow rate of a fluid flowing through the granules packed in the sample for a given pressure drop. However, Carman-Kozeny makes inherent assumptions about tunnel shapes and flow paths that may not accurately hold in situations where the particles possess a wide distribution in shapes, sizes, and aspect ratios, as is true with many powdered systems of technological and commercial interest. To address this challenge, we replicate these measurements virtually on micro-CT images of the powdered material, introducing a new Pore Network Model based on the skeleton of the Morse-Smale complex. Pores are identified as basins of the complex, their incidence encodes adjacency, and the conductivity of the capillary between them is computed from the cross-section at their interface. We build and solve a resistive network to compute an approximate laminar fluid flow through the pore structure. We provide two means of estimating flow-permeable surface area: (i) by direct computation of conductivity, and (ii) by identifying dead-ends in the flow coupled with isosurface extraction and the application of the Carman-Kozeny equation, with the aim of establishing consistency over a range of particle shapes, sizes, porosity levels, and void distribution patterns.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In the study of packed granular materials, the performance of a sample (e.g., the detonation of a high-energy explosive) often correlates to measurements of a fluid flowing through it. The “effective surface area,” the surface area accessible to the airflow, is typically measured using a permeametry apparatus that relates the flow conductance to the permeable surface area via the Carman-Kozeny equation. This equation allows calculating the flow rate of a fluid flowing through the granules packed in the sample for a given pressure drop. However, Carman-Kozeny makes inherent assumptions about tunnel shapes and flow paths that may not accurately hold in situations where the particles possess a wide distribution in shapes, sizes, and aspect ratios, as is true with many powdered systems of technological and commercial interest. To address this challenge, we replicate these measurements virtually on micro-CT images of the powdered material, introducing a new Pore Network Model based on the skeleton of the Morse-Smale complex. Pores are identified as basins of the complex, their incidence encodes adjacency, and the conductivity of the capillary between them is computed from the cross-section at their interface. We build and solve a resistive network to compute an approximate laminar fluid flow through the pore structure. We provide two means of estimating flow-permeable surface area: (i) by direct computation of conductivity, and (ii) by identifying dead-ends in the flow coupled with isosurface extraction and the application of the Carman-Kozeny equation, with the aim of establishing consistency over a range of particle shapes, sizes, porosity levels, and void distribution patterns.",
"title": "Towards replacing physical testing of granular materials with a Topology-based Model",
"normalizedTitle": "Towards replacing physical testing of granular materials with a Topology-based Model",
"fno": "09645370",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Computerised Tomography",
"Flow Simulation",
"Flow Through Porous Media",
"Geophysical Fluid Dynamics",
"Granular Materials",
"Laminar Flow",
"Permeability",
"Porosity",
"Porous Materials",
"Voids Solid",
"Physical Testing",
"Topology Based Model",
"Packed Granular Materials",
"Effective Surface Area",
"Permeametry Apparatus",
"Flow Conductance",
"Carman Kozeny Equation",
"Flow Rate",
"Given Pressure Drop",
"Inherent Assumptions",
"Tunnel Shapes",
"Flow Paths",
"Wide Distribution",
"Aspect Ratios",
"Powdered Systems",
"Technological Interest",
"Commercial Interest",
"Micro CT Images",
"Powdered Material",
"Pore Network Model",
"Morse Smale Complex",
"Approximate Laminar Fluid Flow",
"Pore Structure",
"Flow Permeable Surface Area",
"Particle Shapes",
"Shape",
"Mathematical Models",
"Surface Treatment",
"Powders",
"Computational Modeling",
"Area Measurement",
"Particle Measurements",
"Physical And Environmental Sciences",
"Computational Topology Based Techniques",
"Data Abstractions And Types",
"Scalar Field Data",
"Pore Network Model",
"Morse Smale Complex"
],
"authors": [
{
"givenName": "Aniketh",
"surname": "Venkat",
"fullName": "Aniketh Venkat",
"affiliation": "SCI Institute, University of Utah, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Attila",
"surname": "Gyulassy",
"fullName": "Attila Gyulassy",
"affiliation": "SCI Institute, University of Utah, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Graham",
"surname": "Kosiba",
"fullName": "Graham Kosiba",
"affiliation": "Lawrence Livermore National Laboratory, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Amitesh",
"surname": "Maiti",
"fullName": "Amitesh Maiti",
"affiliation": "Lawrence Livermore National Laboratory, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Henry",
"surname": "Reinstein",
"fullName": "Henry Reinstein",
"affiliation": "Lawrence Livermore National Laboratory, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Richard",
"surname": "Gee",
"fullName": "Richard Gee",
"affiliation": "Lawrence Livermore National Laboratory, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Peer-Timo",
"surname": "Bremer",
"fullName": "Peer-Timo Bremer",
"affiliation": "Lawrence Livermore National Laboratory, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Valerio",
"surname": "Pascucci",
"fullName": "Valerio Pascucci",
"affiliation": "SCI Institute, University of Utah, United States",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "76-85",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/icnc/2008/3304/7/3304g417",
"title": "Cellular Automata Model of Protein Adsorption on the Surface of Bioceramics",
"doi": null,
"abstractUrl": "/proceedings-article/icnc/2008/3304g417/12OmNvCzFbh",
"parentPublication": {
"id": "proceedings/icnc/2008/3304/7",
"title": "2008 Fourth International Conference on Natural Computation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2013/2840/0/2840c952",
"title": "Matching Dry to Wet Materials",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2013/2840c952/12OmNwDj0XK",
"parentPublication": {
"id": "proceedings/iccv/2013/2840/0",
"title": "2013 IEEE International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/crc/2016/3572/0/3572a095",
"title": "The Quality Detection of Surface Defect in Dispensing Dack-End Based on HALCON",
"doi": null,
"abstractUrl": "/proceedings-article/crc/2016/3572a095/12OmNz6iOPB",
"parentPublication": {
"id": "proceedings/crc/2016/3572/0",
"title": "2016 International Conference on Cybernetics, Robotics and Control (CRC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/dac/2002/2402/0/24020552",
"title": "Improving the Generality of the Fictitious Magnetic Charge Approach to Computing Inductances in the Presence of Permeable Materials",
"doi": null,
"abstractUrl": "/proceedings-article/dac/2002/24020552/12OmNzvQHQW",
"parentPublication": {
"id": "proceedings/dac/2002/2402/0",
"title": "Design Automation Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/10/08428445",
"title": "A Semi-Explicit Surface Tracking Mechanism for Multi-Phase Immiscible Liquids",
"doi": null,
"abstractUrl": "/journal/tg/2019/10/08428445/13rRUB7a1g4",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2012/12/ttg2012122149",
"title": "Derived Metric Tensors for Flow Surface Visualization",
"doi": null,
"abstractUrl": "/journal/tg/2012/12/ttg2012122149/13rRUwd9CG1",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2018/08/07964760",
"title": "Real-Time High-Fidelity Surface Flow Simulation",
"doi": null,
"abstractUrl": "/journal/tg/2018/08/07964760/13rRUxDqS8p",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icctec/2017/5784/0/578400a269",
"title": "Study on Hydrophobic Properties Transformation of Texture Surface by Numerical Drop Impact Simulation",
"doi": null,
"abstractUrl": "/proceedings-article/icctec/2017/578400a269/1cks1IQ0pzy",
"parentPublication": {
"id": "proceedings/icctec/2017/5784/0",
"title": "2017 International Conference on Computer Technology, Electronics and Communication (ICCTEC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cw/2019/2297/0/229700a163",
"title": "Simulation Controlling Method for Generating Desired Water Caustics",
"doi": null,
"abstractUrl": "/proceedings-article/cw/2019/229700a163/1fHkljLfIVG",
"parentPublication": {
"id": "proceedings/cw/2019/2297/0",
"title": "2019 International Conference on Cyberworlds (CW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/12/09524524",
"title": "Simulating Multi-Scale, Granular Materials and Their Transitions With a Hybrid Euler-Lagrange Solver",
"doi": null,
"abstractUrl": "/journal/tg/2021/12/09524524/1wpqubOKAne",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552892",
"articleId": "1xibYYzLaWk",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552200",
"articleId": "1xic4fDV0di",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xic4fDV0di",
"doi": "10.1109/TVCG.2021.3114828",
"abstract": "In the process of developing an infrastructure for providing visualization and visual analytics (VIS) tools to epidemiologists and modeling scientists, we encountered a technical challenge for applying a number of visual designs to numerous datasets rapidly and reliably with limited development resources. In this paper, we present a technical solution to address this challenge. Operationally, we separate the tasks of data management, visual designs, and plots and dashboard deployment in order to streamline the development workflow. Technically, we utilize: an ontology to bring datasets, visual designs, and deployable plots and dashboards under the same management framework; multi-criteria search and ranking algorithms for discovering potential datasets that match a visual design; and a purposely-design user interface for propagating each visual design to appropriate datasets (often in tens and hundreds) and quality-assuring the propagation before the deployment. This technical solution has been used in the development of the RAMPVIS infrastructure for supporting a consortium of epidemiologists and modeling scientists through visualization.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In the process of developing an infrastructure for providing visualization and visual analytics (VIS) tools to epidemiologists and modeling scientists, we encountered a technical challenge for applying a number of visual designs to numerous datasets rapidly and reliably with limited development resources. In this paper, we present a technical solution to address this challenge. Operationally, we separate the tasks of data management, visual designs, and plots and dashboard deployment in order to streamline the development workflow. Technically, we utilize: an ontology to bring datasets, visual designs, and deployable plots and dashboards under the same management framework; multi-criteria search and ranking algorithms for discovering potential datasets that match a visual design; and a purposely-design user interface for propagating each visual design to appropriate datasets (often in tens and hundreds) and quality-assuring the propagation before the deployment. This technical solution has been used in the development of the RAMPVIS infrastructure for supporting a consortium of epidemiologists and modeling scientists through visualization.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In the process of developing an infrastructure for providing visualization and visual analytics (VIS) tools to epidemiologists and modeling scientists, we encountered a technical challenge for applying a number of visual designs to numerous datasets rapidly and reliably with limited development resources. In this paper, we present a technical solution to address this challenge. Operationally, we separate the tasks of data management, visual designs, and plots and dashboard deployment in order to streamline the development workflow. Technically, we utilize: an ontology to bring datasets, visual designs, and deployable plots and dashboards under the same management framework; multi-criteria search and ranking algorithms for discovering potential datasets that match a visual design; and a purposely-design user interface for propagating each visual design to appropriate datasets (often in tens and hundreds) and quality-assuring the propagation before the deployment. This technical solution has been used in the development of the RAMPVIS infrastructure for supporting a consortium of epidemiologists and modeling scientists through visualization.",
"title": "Propagating Visual Designs to Numerous Plots and Dashboards",
"normalizedTitle": "Propagating Visual Designs to Numerous Plots and Dashboards",
"fno": "09552200",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Data Visualization",
"Visualization",
"Ontologies",
"Tools",
"Programming",
"Analytical Models",
"Time Series Analysis",
"Visualization System",
"Propagation",
"Infrastructure",
"Ontology",
"Quality Assurance",
"Pandemic",
"Emergency Response"
],
"authors": [
{
"givenName": "Saiful",
"surname": "Khan",
"fullName": "Saiful Khan",
"affiliation": "University of Oxford, UK",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Phong H.",
"surname": "Nguyen",
"fullName": "Phong H. Nguyen",
"affiliation": "Redsift Ltd., UK",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Alfie",
"surname": "Abdul-Rahman",
"fullName": "Alfie Abdul-Rahman",
"affiliation": "King's College London, UK",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Benjamin",
"surname": "Bach",
"fullName": "Benjamin Bach",
"affiliation": "Edinburgh University, UK",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Min",
"surname": "Chen",
"fullName": "Min Chen",
"affiliation": "University of Oxford, UK",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Euan",
"surname": "Freeman",
"fullName": "Euan Freeman",
"affiliation": "University of Glasgow, Scotland",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Cagatay",
"surname": "Turkay",
"fullName": "Cagatay Turkay",
"affiliation": "University of Warwick, UK",
"__typename": "ArticleAuthorType"
}
],
"replicability": {
"isEnabled": false,
"codeDownloadUrl": "https://github.com/saifulkhan/rampvis-ontology-management-ui.git",
"codeRepositoryUrl": "https://github.com/saifulkhan/rampvis-ontology-management-ui",
"__typename": "ArticleReplicabilityType"
},
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "86-95",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/cerma/2008/3320/0/3320a183",
"title": "RecurrenceVs: A Software Tool for Analysis of Similarity in Recurrence Plots",
"doi": null,
"abstractUrl": "/proceedings-article/cerma/2008/3320a183/12OmNAkWvl2",
"parentPublication": {
"id": "proceedings/cerma/2008/3320/0",
"title": "Electronics, Robotics and Automotive Mechanics Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdar/2015/1805/0/07333871",
"title": "Automated analysis of line plots in documents",
"doi": null,
"abstractUrl": "/proceedings-article/icdar/2015/07333871/12OmNBOCWfV",
"parentPublication": {
"id": "proceedings/icdar/2015/1805/0",
"title": "2015 13th International Conference on Document Analysis and Recognition (ICDAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pacificvis/2017/5738/0/08031609",
"title": "Making many-to-many parallel coordinate plots scalable by asymmetric biclustering",
"doi": null,
"abstractUrl": "/proceedings-article/pacificvis/2017/08031609/12OmNrHjqNa",
"parentPublication": {
"id": "proceedings/pacificvis/2017/5738/0",
"title": "2017 IEEE Pacific Visualization Symposium (PacificVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vahc/2017/3187/0/08387496",
"title": "DataScope: Interactive visual exploratory dashboards for large multidimensional data",
"doi": null,
"abstractUrl": "/proceedings-article/vahc/2017/08387496/12OmNx4Q6FM",
"parentPublication": {
"id": "proceedings/vahc/2017/3187/0",
"title": "2017 IEEE Workshop on Visual Analytics in Healthcare (VAHC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cgiv/2017/0852/0/0852a099",
"title": "Stem & Leaf Plots Extended for Text Visualizations",
"doi": null,
"abstractUrl": "/proceedings-article/cgiv/2017/0852a099/12OmNy5zspa",
"parentPublication": {
"id": "proceedings/cgiv/2017/0852/0",
"title": "2017 14th International Conference on Computer Graphics, Imaging and Visualization (CGiV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2016/01/07192696",
"title": "Orientation-Enhanced Parallel Coordinate Plots",
"doi": null,
"abstractUrl": "/journal/tg/2016/01/07192696/13rRUwkxc5q",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/06/08667672",
"title": "Relaxing Dense Scatter Plots with Pixel-Based Mappings",
"doi": null,
"abstractUrl": "/journal/tg/2019/06/08667672/18q6mW4N2ZW",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vis/2019/4941/0/08933582",
"title": "Periphery Plots for Contextualizing Heterogeneous Time-Based Charts",
"doi": null,
"abstractUrl": "/proceedings-article/vis/2019/08933582/1fTgIueMC7m",
"parentPublication": {
"id": "proceedings/vis/2019/4941/0",
"title": "2019 IEEE Visualization Conference (VIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacv/2020/6553/0/09093523",
"title": "PlotQA: Reasoning over Scientific Plots",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2020/09093523/1jPbuLQHNhm",
"parentPublication": {
"id": "proceedings/wacv/2020/6553/0",
"title": "2020 IEEE Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pacificvis/2020/5697/0/09086292",
"title": "Space-Reclaiming Icicle Plots",
"doi": null,
"abstractUrl": "/proceedings-article/pacificvis/2020/09086292/1kuHnGGBnBS",
"parentPublication": {
"id": "proceedings/pacificvis/2020/5697/0",
"title": "2020 IEEE Pacific Visualization Symposium (PacificVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09645370",
"articleId": "1zc6D7Qkucw",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09559731",
"articleId": "1xs9BhiH0HK",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBaO1Ado1G",
"name": "ttg202201-09552200s1-supp1-3114828.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552200s1-supp1-3114828.mp4",
"extension": "mp4",
"size": "33.4 MB",
"__typename": "WebExtraType"
},
{
"id": "1zBaNVG2Qes",
"name": "ttg202201-09552200s1-supp2-3114828.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552200s1-supp2-3114828.pdf",
"extension": "pdf",
"size": "397 kB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xs9BhiH0HK",
"doi": "10.1109/TVCG.2021.3114798",
"abstract": "Personal informatics research helps people track personal data for the purposes of self-reflection and gaining self-knowledge. This field, however, has predominantly focused on the data collection and insight-generation elements of self-tracking, with less attention paid to flexible data analysis. As a result, this inattention has led to inflexible analytic pipelines that do not reflect or support the diverse ways people want to engage with their data. This paper contributes a review of personal informatics and visualization research literature to expose a gap in our knowledge for designing flexible tools that assist people engaging with and analyzing personal data in personal contexts, what we call the personal informatics analysis gap. We explore this gap through a multistage longitudinal study on how asthmatics engage with personal air quality data, and we report how participants: were motivated by broad and diverse goals; exhibited patterns in the way they explored their data; engaged with their data in playful ways; discovered new insights through serendipitous exploration; and were reluctant to use analysis tools on their own. These results present new opportunities for visual analysis research and suggest the need for fundamental shifts in how and what we design when supporting personal data analysis.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Personal informatics research helps people track personal data for the purposes of self-reflection and gaining self-knowledge. This field, however, has predominantly focused on the data collection and insight-generation elements of self-tracking, with less attention paid to flexible data analysis. As a result, this inattention has led to inflexible analytic pipelines that do not reflect or support the diverse ways people want to engage with their data. This paper contributes a review of personal informatics and visualization research literature to expose a gap in our knowledge for designing flexible tools that assist people engaging with and analyzing personal data in personal contexts, what we call the personal informatics analysis gap. We explore this gap through a multistage longitudinal study on how asthmatics engage with personal air quality data, and we report how participants: were motivated by broad and diverse goals; exhibited patterns in the way they explored their data; engaged with their data in playful ways; discovered new insights through serendipitous exploration; and were reluctant to use analysis tools on their own. These results present new opportunities for visual analysis research and suggest the need for fundamental shifts in how and what we design when supporting personal data analysis.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Personal informatics research helps people track personal data for the purposes of self-reflection and gaining self-knowledge. This field, however, has predominantly focused on the data collection and insight-generation elements of self-tracking, with less attention paid to flexible data analysis. As a result, this inattention has led to inflexible analytic pipelines that do not reflect or support the diverse ways people want to engage with their data. This paper contributes a review of personal informatics and visualization research literature to expose a gap in our knowledge for designing flexible tools that assist people engaging with and analyzing personal data in personal contexts, what we call the personal informatics analysis gap. We explore this gap through a multistage longitudinal study on how asthmatics engage with personal air quality data, and we report how participants: were motivated by broad and diverse goals; exhibited patterns in the way they explored their data; engaged with their data in playful ways; discovered new insights through serendipitous exploration; and were reluctant to use analysis tools on their own. These results present new opportunities for visual analysis research and suggest the need for fundamental shifts in how and what we design when supporting personal data analysis.",
"title": "Exploring the Personal Informatics Analysis Gap: “There's a Lot of Bacon”",
"normalizedTitle": "Exploring the Personal Informatics Analysis Gap: “There's a Lot of Bacon”",
"fno": "09559731",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Data Analysis",
"Data Privacy",
"Data Visualisation",
"Personal Air Quality Data",
"Visual Analysis Research",
"Personal Data Analysis",
"Personal Informatics Analysis Gap",
"Personal Informatics Research",
"Self Reflection",
"Gaining Self Knowledge",
"Data Collection",
"Insight Generation Elements",
"Flexible Data Analysis",
"Diverse Ways People",
"Visualization Research Literature",
"Personal Contexts",
"Informatics",
"Tools",
"Data Visualization",
"Data Analysis",
"Task Analysis",
"Context",
"Analytical Models",
"Personal Visualization",
"Personal Visual Analytics",
"Personal Informatics",
"Interview Methods"
],
"authors": [
{
"givenName": "Jimmy",
"surname": "Moore",
"fullName": "Jimmy Moore",
"affiliation": "School of Computing at the Univeristy of Utah, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Pascal",
"surname": "Goffin",
"fullName": "Pascal Goffin",
"affiliation": "Asvito Digital AG., Switzerland",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jason",
"surname": "Wiese",
"fullName": "Jason Wiese",
"affiliation": "School of Computing at the Univeristy of Utah, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Miriah",
"surname": "Meyer",
"fullName": "Miriah Meyer",
"affiliation": "Department of Science and Technology at Linköping University, School of Computing at the University of Utah, United States",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "96-106",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/ichi/2015/9548/0/9548a444",
"title": "Data Analytics in Healthcare Informatics",
"doi": null,
"abstractUrl": "/proceedings-article/ichi/2015/9548a444/12OmNAnMuv6",
"parentPublication": {
"id": "proceedings/ichi/2015/9548/0",
"title": "2015 International Conference on Healthcare Informatics (ICHI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hicss/2015/7367/0/7367e938",
"title": "Exploring the Impact of IS Theory on Health Informatics",
"doi": null,
"abstractUrl": "/proceedings-article/hicss/2015/7367e938/12OmNvTTcg4",
"parentPublication": {
"id": "proceedings/hicss/2015/7367/0",
"title": "2015 48th Hawaii International Conference on System Sciences (HICSS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/srii/2011/4371/0/4371a357",
"title": "Domain Ontology Health Informatics Service from Text Medical Data Classification",
"doi": null,
"abstractUrl": "/proceedings-article/srii/2011/4371a357/12OmNx0RIXS",
"parentPublication": {
"id": "proceedings/srii/2011/4371/0",
"title": "Annual SRII Global Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2017/3050/0/08217732",
"title": "Collaborations across disciplines: MU thyroid nodule electronic database (MU-TNED), a multidisciplinary informatics approach",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2017/08217732/12OmNyQpgQd",
"parentPublication": {
"id": "proceedings/bibm/2017/3050/0",
"title": "2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cs/2003/03/c3032",
"title": "How trees and forests inform biodiversity and ecosystem informatics",
"doi": null,
"abstractUrl": "/magazine/cs/2003/03/c3032/13rRUEgs2F4",
"parentPublication": {
"id": "mags/cs",
"title": "Computing in Science & Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2017/04/07420655",
"title": "Omics Informatics: From Scattered Individual Software Tools to Integrated Workflow Management Systems",
"doi": null,
"abstractUrl": "/journal/tb/2017/04/07420655/13rRUEgs2Kp",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cs/2013/05/mcs2013050032",
"title": "Climate Informatics: Accelerating Discovering in Climate Science with Machine Learning",
"doi": null,
"abstractUrl": "/magazine/cs/2013/05/mcs2013050032/13rRUy2YLOR",
"parentPublication": {
"id": "mags/cs",
"title": "Computing in Science & Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/co/2014/01/mco2014010078",
"title": "Privacy Informatics: A Primer on Defensive Tactics for a Society under Siege",
"doi": null,
"abstractUrl": "/magazine/co/2014/01/mco2014010078/13rRUypp5bu",
"parentPublication": {
"id": "mags/co",
"title": "Computer",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aiccsa/2018/9120/0/08612876",
"title": "Design and Development of Case Studies in Security and Privacy for Health Informatics Education",
"doi": null,
"abstractUrl": "/proceedings-article/aiccsa/2018/08612876/17D45Xh13vn",
"parentPublication": {
"id": "proceedings/aiccsa/2018/9120/0",
"title": "2018 IEEE/ACS 15th International Conference on Computer Systems and Applications (AICCSA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cloudcom/2019/5011/0/501100a313",
"title": "Activity Monitor A Personal Informatics Application",
"doi": null,
"abstractUrl": "/proceedings-article/cloudcom/2019/501100a313/1h0Kwmo8Q6Y",
"parentPublication": {
"id": "proceedings/cloudcom/2019/5011/0",
"title": "2019 IEEE International Conference on Cloud Computing Technology and Science (CloudCom)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552200",
"articleId": "1xic4fDV0di",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552238",
"articleId": "1xic77YygOk",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBaGD63W0M",
"name": "ttg202201-09559731s1-tvcg-3114798-mm.zip",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09559731s1-tvcg-3114798-mm.zip",
"extension": "zip",
"size": "4.24 kB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xic77YygOk",
"doi": "10.1109/TVCG.2021.3114835",
"abstract": "Situated visualization is an emerging concept within visualization, in which data is visualized in situ, where it is relevant to people. The concept has gained interest from multiple research communities, including visualization, human-computer interaction (HCI) and augmented reality. This has led to a range of explorations and applications of the concept, however, this early work has focused on the operational aspect of situatedness leading to inconsistent adoption of the concept and terminology. First, we contribute a literature survey in which we analyze 44 papers that explicitly use the term “situated visualization” to provide an overview of the research area, how it defines situated visualization, common application areas and technology used, as well as type of data and type of visualizations. Our survey shows that research on situated visualization has focused on technology-centric approaches that foreground a spatial understanding of situatedness. Secondly, we contribute five perspectives on situatedness (space, time, place, activity, and community) that together expand on the prevalent notion of situatedness in the corpus. We draw from six case studies and prior theoretical developments in HCI. Each perspective develops a generative way of looking at and working with situatedness in design and research. We outline future directions, including considering technology, material and aesthetics, leveraging the perspectives for design, and methods for stronger engagement with target audiences. We conclude with opportunities to consolidate situated visualization research.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Situated visualization is an emerging concept within visualization, in which data is visualized in situ, where it is relevant to people. The concept has gained interest from multiple research communities, including visualization, human-computer interaction (HCI) and augmented reality. This has led to a range of explorations and applications of the concept, however, this early work has focused on the operational aspect of situatedness leading to inconsistent adoption of the concept and terminology. First, we contribute a literature survey in which we analyze 44 papers that explicitly use the term “situated visualization” to provide an overview of the research area, how it defines situated visualization, common application areas and technology used, as well as type of data and type of visualizations. Our survey shows that research on situated visualization has focused on technology-centric approaches that foreground a spatial understanding of situatedness. Secondly, we contribute five perspectives on situatedness (space, time, place, activity, and community) that together expand on the prevalent notion of situatedness in the corpus. We draw from six case studies and prior theoretical developments in HCI. Each perspective develops a generative way of looking at and working with situatedness in design and research. We outline future directions, including considering technology, material and aesthetics, leveraging the perspectives for design, and methods for stronger engagement with target audiences. We conclude with opportunities to consolidate situated visualization research.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Situated visualization is an emerging concept within visualization, in which data is visualized in situ, where it is relevant to people. The concept has gained interest from multiple research communities, including visualization, human-computer interaction (HCI) and augmented reality. This has led to a range of explorations and applications of the concept, however, this early work has focused on the operational aspect of situatedness leading to inconsistent adoption of the concept and terminology. First, we contribute a literature survey in which we analyze 44 papers that explicitly use the term “situated visualization” to provide an overview of the research area, how it defines situated visualization, common application areas and technology used, as well as type of data and type of visualizations. Our survey shows that research on situated visualization has focused on technology-centric approaches that foreground a spatial understanding of situatedness. Secondly, we contribute five perspectives on situatedness (space, time, place, activity, and community) that together expand on the prevalent notion of situatedness in the corpus. We draw from six case studies and prior theoretical developments in HCI. Each perspective develops a generative way of looking at and working with situatedness in design and research. We outline future directions, including considering technology, material and aesthetics, leveraging the perspectives for design, and methods for stronger engagement with target audiences. We conclude with opportunities to consolidate situated visualization research.",
"title": "What's the Situation with Situated Visualization? A Survey and Perspectives on Situatedness",
"normalizedTitle": "What's the Situation with Situated Visualization? A Survey and Perspectives on Situatedness",
"fno": "09552238",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Data Visualization",
"Human Computer Interaction",
"Encoding",
"Visual Analytics",
"Terminology",
"Keyword Search",
"Augmented Reality",
"Situated Visualization",
"Literature Survey",
"Situatedness"
],
"authors": [
{
"givenName": "Nathalie",
"surname": "Bressa",
"fullName": "Nathalie Bressa",
"affiliation": "Aarhus University, Denmark",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Henrik",
"surname": "Korsgaard",
"fullName": "Henrik Korsgaard",
"affiliation": "Aarhus University, Denmark",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Aurélien",
"surname": "Tabard",
"fullName": "Aurélien Tabard",
"affiliation": "Université Claude Bernard Lyon 1, LIRIS, CNRS UMR5205, France",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Steven",
"surname": "Houben",
"fullName": "Steven Houben",
"affiliation": "Eindhoven University of Technology, Netherlands",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jo",
"surname": "Vermeulen",
"fullName": "Jo Vermeulen",
"affiliation": "Autodesk Research, Canada",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "107-117",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/iv/2011/0868/0/06004062",
"title": "What is Knowledge Visualization? Perspectives on an Emerging Discipline",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2011/06004062/12OmNAsTgVr",
"parentPublication": {
"id": "proceedings/iv/2011/0868/0",
"title": "2011 15th International Conference on Information Visualisation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2010/7846/0/05571207",
"title": "Immersive Visualization Architectures and Situated Embodiments of Culture and Heritage",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2010/05571207/12OmNwFid56",
"parentPublication": {
"id": "proceedings/iv/2010/7846/0",
"title": "2010 14th International Conference Information Visualisation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2015/1727/0/07223352",
"title": "Using augmented reality to support situated analytics",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2015/07223352/12OmNzhELmY",
"parentPublication": {
"id": "proceedings/vr/2015/1727/0",
"title": "2015 IEEE Virtual Reality (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2018/3365/0/08446212",
"title": "Towards Situated Knee Trajectory Visualization for Self Analysis in Cycling",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2018/08446212/13bd1fHrlRw",
"parentPublication": {
"id": "proceedings/vr/2018/3365/0",
"title": "2018 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2017/01/07536110",
"title": "Annotation Graphs: A Graph-Based Visualization for Meta-Analysis of Data Based on User-Authored Annotations",
"doi": null,
"abstractUrl": "/journal/tg/2017/01/07536110/13rRUxZ0o1F",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vrw/2022/8402/0/840200a472",
"title": "Situated Visualization of IIoT Data on the Hololens 2",
"doi": null,
"abstractUrl": "/proceedings-article/vrw/2022/840200a472/1CJend8tNew",
"parentPublication": {
"id": "proceedings/vrw/2022/8402/0",
"title": "2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09904883",
"title": "Effects of View Layout on Situated Analytics for Multiple-View Representations in Immersive Visualization",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09904883/1H2lc7qemsg",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2020/01/08805424",
"title": "What is Interaction for Data Visualization?",
"doi": null,
"abstractUrl": "/journal/tg/2020/01/08805424/1cG4MsovTO0",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2019/2838/0/283800a013",
"title": "Situated Visualization in The Decision Process Through Augmented Reality",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2019/283800a013/1cMF8HeJlW8",
"parentPublication": {
"id": "proceedings/iv/2019/2838/0",
"title": "2019 23rd International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vrw/2021/4057/0/405700a721",
"title": "[DC] Situated augmented reality: beyond the egocentric viewpoint",
"doi": null,
"abstractUrl": "/proceedings-article/vrw/2021/405700a721/1tnWQUIqzza",
"parentPublication": {
"id": "proceedings/vrw/2021/4057/0",
"title": "2021 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09559731",
"articleId": "1xs9BhiH0HK",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09557225",
"articleId": "1xlvZlGiUsE",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBaX5fyCuA",
"name": "ttg202201-09552238s1-supp1-3114835.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552238s1-supp1-3114835.pdf",
"extension": "pdf",
"size": "438 kB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xlvZlGiUsE",
"doi": "10.1109/TVCG.2021.3114861",
"abstract": "Tactic analysis is a major issue in badminton as the effective usage of tactics is the key to win. The tactic in badminton is defined as a sequence of consecutive strokes. Most existing methods use statistical models to find sequential patterns of strokes and apply 2D visualizations such as glyphs and statistical charts to explore and analyze the discovered patterns. However, in badminton, spatial information like the shuttle trajectory, which is inherently 3D, is the core of a tactic. The lack of sufficient spatial awareness in 2D visualizations largely limited the tactic analysis of badminton. In this work, we collaborate with domain experts to study the tactic analysis of badminton in a 3D environment and propose an immersive visual analytics system, TIVEE, to assist users in exploring and explaining badminton tactics from multi-levels. Users can first explore various tactics from the third-person perspective using an unfolded visual presentation of stroke sequences. By selecting a tactic of interest, users can turn to the first-person perspective to perceive the detailed kinematic characteristics and explain its effects on the game result. The effectiveness and usefulness of TIVEE are demonstrated by case studies and an expert interview.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Tactic analysis is a major issue in badminton as the effective usage of tactics is the key to win. The tactic in badminton is defined as a sequence of consecutive strokes. Most existing methods use statistical models to find sequential patterns of strokes and apply 2D visualizations such as glyphs and statistical charts to explore and analyze the discovered patterns. However, in badminton, spatial information like the shuttle trajectory, which is inherently 3D, is the core of a tactic. The lack of sufficient spatial awareness in 2D visualizations largely limited the tactic analysis of badminton. In this work, we collaborate with domain experts to study the tactic analysis of badminton in a 3D environment and propose an immersive visual analytics system, TIVEE, to assist users in exploring and explaining badminton tactics from multi-levels. Users can first explore various tactics from the third-person perspective using an unfolded visual presentation of stroke sequences. By selecting a tactic of interest, users can turn to the first-person perspective to perceive the detailed kinematic characteristics and explain its effects on the game result. The effectiveness and usefulness of TIVEE are demonstrated by case studies and an expert interview.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Tactic analysis is a major issue in badminton as the effective usage of tactics is the key to win. The tactic in badminton is defined as a sequence of consecutive strokes. Most existing methods use statistical models to find sequential patterns of strokes and apply 2D visualizations such as glyphs and statistical charts to explore and analyze the discovered patterns. However, in badminton, spatial information like the shuttle trajectory, which is inherently 3D, is the core of a tactic. The lack of sufficient spatial awareness in 2D visualizations largely limited the tactic analysis of badminton. In this work, we collaborate with domain experts to study the tactic analysis of badminton in a 3D environment and propose an immersive visual analytics system, TIVEE, to assist users in exploring and explaining badminton tactics from multi-levels. Users can first explore various tactics from the third-person perspective using an unfolded visual presentation of stroke sequences. By selecting a tactic of interest, users can turn to the first-person perspective to perceive the detailed kinematic characteristics and explain its effects on the game result. The effectiveness and usefulness of TIVEE are demonstrated by case studies and an expert interview.",
"title": "TIVEE: Visual Exploration and Explanation of Badminton Tactics in Immersive Visualizations",
"normalizedTitle": "TIVEE: Visual Exploration and Explanation of Badminton Tactics in Immersive Visualizations",
"fno": "09557225",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Trajectory",
"Sports",
"Three Dimensional Displays",
"Data Visualization",
"Visualization",
"Games",
"Layout",
"Tactic Analysis",
"Stroke Sequence Visualization",
"Immersive Visualization"
],
"authors": [
{
"givenName": "Xiangtong",
"surname": "Chu",
"fullName": "Xiangtong Chu",
"affiliation": "State Key Lab of CAD&CG, Zhejiang University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Xiao",
"surname": "Xie",
"fullName": "Xiao Xie",
"affiliation": "Department of Sport Science, Zhejiang University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Shuainan",
"surname": "Ye",
"fullName": "Shuainan Ye",
"affiliation": "State Key Lab of CAD&CG, Zhejiang University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Haolin",
"surname": "Lu",
"fullName": "Haolin Lu",
"affiliation": "State Key Lab of CAD&CG, Zhejiang University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Hongguang",
"surname": "Xiao",
"fullName": "Hongguang Xiao",
"affiliation": "State Key Lab of CAD&CG, Zhejiang University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Zeqing",
"surname": "Yuan",
"fullName": "Zeqing Yuan",
"affiliation": "State Key Lab of CAD&CG, Zhejiang University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Zhutian",
"surname": "Chen",
"fullName": "Zhutian Chen",
"affiliation": "Department of Cognitive Science and Design Lab, University of California San Diego, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Hui",
"surname": "Zhang",
"fullName": "Hui Zhang",
"affiliation": "Department of Sport Science, Zhejiang University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yingcai",
"surname": "Wu",
"fullName": "Yingcai Wu",
"affiliation": "State Key Lab of CAD&CG, Zhejiang University, China",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "118-128",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/wacv/2018/4886/0/488601a296",
"title": "Towards Structured Analysis of Broadcast Badminton Videos",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2018/488601a296/12OmNAio70r",
"parentPublication": {
"id": "proceedings/wacv/2018/4886/0",
"title": "2018 IEEE Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvprw/2017/0733/0/0733a132",
"title": "Application of Computer Vision and Vector Space Model for Tactical Movement Classification in Badminton",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2017/0733a132/12OmNBuL15s",
"parentPublication": {
"id": "proceedings/cvprw/2017/0733/0",
"title": "2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2022/8563/0/09859960",
"title": "Learning Robust Latent Space of Basketball Player Trajectories for Tactics Analysis",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2022/09859960/1G9EGpU5iZW",
"parentPublication": {
"id": "proceedings/icme/2022/8563/0",
"title": "2022 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09906966",
"title": "RASIPAM: Interactive Pattern Mining of Multivariate Event Sequences in Racket Sports",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09906966/1H5ERCYJa48",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ickg/2022/5101/0/510100a337",
"title": "VREN: Volleyball Rally Dataset with Expression Notation Language",
"doi": null,
"abstractUrl": "/proceedings-article/ickg/2022/510100a337/1KxU3tQFoPK",
"parentPublication": {
"id": "proceedings/ickg/2022/5101/0",
"title": "2022 IEEE International Conference on Knowledge Graph (ICKG)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/02/09222313",
"title": "ShuttleSpace: Exploring and Analyzing Movement Trajectory in Immersive Visualization",
"doi": null,
"abstractUrl": "/journal/tg/2021/02/09222313/1nTr29xEpkk",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/08/09303392",
"title": "Feasibility Study on Virtual Reality Based Basketball Tactic Training",
"doi": null,
"abstractUrl": "/journal/tg/2022/08/09303392/1pLFQxpKDIY",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vast/2020/8009/0/800900a036",
"title": "Visual Analytics of Multivariate Event Sequence Data in Racquet Sports",
"doi": null,
"abstractUrl": "/proceedings-article/vast/2020/800900a036/1q7jwkJx00U",
"parentPublication": {
"id": "proceedings/vast/2020/8009/0",
"title": "2020 IEEE Conference on Visual Analytics Science and Technology (VAST)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/06/09411869",
"title": "Tac-Miner: Visual Tactic Mining for Multiple Table Tennis Matches",
"doi": null,
"abstractUrl": "/journal/tg/2021/06/09411869/1t2ii7r7RcI",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/01/09552436",
"title": "TacticFlow: Visual Analytics of Ever-Changing Tactics in Racket Sports",
"doi": null,
"abstractUrl": "/journal/tg/2022/01/09552436/1xibYczQBfW",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552238",
"articleId": "1xic77YygOk",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552592",
"articleId": "1xic0SUdCNO",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xic0SUdCNO",
"doi": "10.1109/TVCG.2021.3114782",
"abstract": "Authors often transform a large screen visualization for smaller displays through rescaling, aggregation and other techniques when creating visualizations for both desktop and mobile devices (i.e., responsive visualization). However, transformations can alter relationships or patterns implied by the large screen view, requiring authors to reason carefully about what information to preserve while adjusting their design for the smaller display. We propose an automated approach to approximating the loss of support for task-oriented visualization insights (identification, comparison, and trend) in responsive transformation of a source visualization. We operationalize identification, comparison, and trend loss as objective functions calculated by comparing properties of the rendered source visualization to each realized target (small screen) visualization. To evaluate the utility of our approach, we train machine learning models on human ranked small screen alternative visualizations across a set of source visualizations. We find that our approach achieves an accuracy of 84% (random forest model) in ranking visualizations. We demonstrate this approach in a prototype responsive visualization recommender that enumerates responsive transformations using Answer Set Programming and evaluates the preservation of task-oriented insights using our loss measures. We discuss implications of our approach for the development of automated and semi-automated responsive visualization recommendation.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Authors often transform a large screen visualization for smaller displays through rescaling, aggregation and other techniques when creating visualizations for both desktop and mobile devices (i.e., responsive visualization). However, transformations can alter relationships or patterns implied by the large screen view, requiring authors to reason carefully about what information to preserve while adjusting their design for the smaller display. We propose an automated approach to approximating the loss of support for task-oriented visualization insights (identification, comparison, and trend) in responsive transformation of a source visualization. We operationalize identification, comparison, and trend loss as objective functions calculated by comparing properties of the rendered source visualization to each realized target (small screen) visualization. To evaluate the utility of our approach, we train machine learning models on human ranked small screen alternative visualizations across a set of source visualizations. We find that our approach achieves an accuracy of 84% (random forest model) in ranking visualizations. We demonstrate this approach in a prototype responsive visualization recommender that enumerates responsive transformations using Answer Set Programming and evaluates the preservation of task-oriented insights using our loss measures. We discuss implications of our approach for the development of automated and semi-automated responsive visualization recommendation.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Authors often transform a large screen visualization for smaller displays through rescaling, aggregation and other techniques when creating visualizations for both desktop and mobile devices (i.e., responsive visualization). However, transformations can alter relationships or patterns implied by the large screen view, requiring authors to reason carefully about what information to preserve while adjusting their design for the smaller display. We propose an automated approach to approximating the loss of support for task-oriented visualization insights (identification, comparison, and trend) in responsive transformation of a source visualization. We operationalize identification, comparison, and trend loss as objective functions calculated by comparing properties of the rendered source visualization to each realized target (small screen) visualization. To evaluate the utility of our approach, we train machine learning models on human ranked small screen alternative visualizations across a set of source visualizations. We find that our approach achieves an accuracy of 84% (random forest model) in ranking visualizations. We demonstrate this approach in a prototype responsive visualization recommender that enumerates responsive transformations using Answer Set Programming and evaluates the preservation of task-oriented insights using our loss measures. We discuss implications of our approach for the development of automated and semi-automated responsive visualization recommendation.",
"title": "An Automated Approach to Reasoning About Task-Oriented Insights in Responsive Visualization",
"normalizedTitle": "An Automated Approach to Reasoning About Task-Oriented Insights in Responsive Visualization",
"fno": "09552592",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Visualization",
"Data Visualization",
"Task Analysis",
"Loss Measurement",
"Encoding",
"Economic Indicators",
"Market Research",
"Task Oriented Insight Preservation",
"Responsive Visualization"
],
"authors": [
{
"givenName": "Hyeok",
"surname": "Kim",
"fullName": "Hyeok Kim",
"affiliation": "Northwestern University, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Ryan",
"surname": "Rossi",
"fullName": "Ryan Rossi",
"affiliation": "Adobe Research, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Abhraneel",
"surname": "Sarma",
"fullName": "Abhraneel Sarma",
"affiliation": "Northwestern University, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Dominik",
"surname": "Moritz",
"fullName": "Dominik Moritz",
"affiliation": "Carnegie Mellon University, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jessica",
"surname": "Hullman",
"fullName": "Jessica Hullman",
"affiliation": "Northwestern University, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "129-139",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/ieee-vis/1998/9176/0/91760463",
"title": "Battlefield Visualization on the Responsive Workbench",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-vis/1998/91760463/12OmNwwd2KP",
"parentPublication": {
"id": "proceedings/ieee-vis/1998/9176/0",
"title": "Visualization Conference, IEEE",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ldav/2011/0155/0/06092338",
"title": "Evolving a rapid prototyping environment for visually and analytically exploring large-scale Linked Open Data",
"doi": null,
"abstractUrl": "/proceedings-article/ldav/2011/06092338/12OmNx19k34",
"parentPublication": {
"id": "proceedings/ldav/2011/0155/0",
"title": "IEEE Symposium on Large Data Analysis and Visualization (LDAV 2011)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2014/12/06876042",
"title": "iVisDesigner: Expressive Interactive Design of Information Visualizations",
"doi": null,
"abstractUrl": "/journal/tg/2014/12/06876042/13rRUwI5U2H",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/2015/04/mcg2015040028",
"title": "Characterizing Visualization Insights from Quantified Selfers' Personal Data Presentations",
"doi": null,
"abstractUrl": "/magazine/cg/2015/04/mcg2015040028/13rRUxCRFQl",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icst/2022/6679/0/667900a140",
"title": "Automated Repair of Responsive Web Page Layouts",
"doi": null,
"abstractUrl": "/proceedings-article/icst/2022/667900a140/1E2wEvLyhA4",
"parentPublication": {
"id": "proceedings/icst/2022/6679/0",
"title": "2022 IEEE Conference on Software Testing, Verification and Validation (ICST)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09904451",
"title": "Multi-View Design Patterns and Responsive Visualization for Genomics Data",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09904451/1H1gfVbEsiA",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/10029921",
"title": "Semi-Automatic Layout Adaptation for Responsive Multiple-View Visualization Design",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/10029921/1KmyX4gJuMg",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacv/2020/6553/0/09093469",
"title": "2-MAP: Aligned Visualizations for Comparison of High-Dimensional Point Sets",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2020/09093469/1jPbpOaFbRC",
"parentPublication": {
"id": "proceedings/wacv/2020/6553/0",
"title": "2020 IEEE Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/02/09226461",
"title": "Responsive Matrix Cells: A Focus+Context Approach for Exploring and Editing Multivariate Graphs",
"doi": null,
"abstractUrl": "/journal/tg/2021/02/09226461/1nYrgS8Y9Py",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/03/09275378",
"title": "Task-Based Effectiveness of Interactive Contiguous Area Cartograms",
"doi": null,
"abstractUrl": "/journal/tg/2021/03/09275378/1pcOsFJxDYQ",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09557225",
"articleId": "1xlvZlGiUsE",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09557192",
"articleId": "1xlw1UFWxDa",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBaCe0fdao",
"name": "ttg202201-09552592s1-tvcg-3114782-mm.zip",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552592s1-tvcg-3114782-mm.zip",
"extension": "zip",
"size": "2.15 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xlw1UFWxDa",
"doi": "10.1109/TVCG.2021.3114876",
"abstract": "The combination of diverse data types and analysis tasks in genomics has resulted in the development of a wide range of visualization techniques and tools. However, most existing tools are tailored to a specific problem or data type and offer limited customization, making it challenging to optimize visualizations for new analysis tasks or datasets. To address this challenge, we designed Gosling-a grammar for interactive and scalable genomics data visualization. Gosling balances expressiveness for comprehensive multi-scale genomics data visualizations with accessibility for domain scientists. Our accompanying JavaScript toolkit called Gosling.js provides scalable and interactive rendering. Gosling.js is built on top of an existing platform for web-based genomics data visualization to further simplify the visualization of common genomics data formats. We demonstrate the expressiveness of the grammar through a variety of real-world examples. Furthermore, we show how Gosling supports the design of novel genomics visualizations. An online editor and examples of Gosling.js, its source code, and documentation are available at <uri>https://gosling.js.org</uri>.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The combination of diverse data types and analysis tasks in genomics has resulted in the development of a wide range of visualization techniques and tools. However, most existing tools are tailored to a specific problem or data type and offer limited customization, making it challenging to optimize visualizations for new analysis tasks or datasets. To address this challenge, we designed Gosling-a grammar for interactive and scalable genomics data visualization. Gosling balances expressiveness for comprehensive multi-scale genomics data visualizations with accessibility for domain scientists. Our accompanying JavaScript toolkit called Gosling.js provides scalable and interactive rendering. Gosling.js is built on top of an existing platform for web-based genomics data visualization to further simplify the visualization of common genomics data formats. We demonstrate the expressiveness of the grammar through a variety of real-world examples. Furthermore, we show how Gosling supports the design of novel genomics visualizations. An online editor and examples of Gosling.js, its source code, and documentation are available at <uri>https://gosling.js.org</uri>.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "The combination of diverse data types and analysis tasks in genomics has resulted in the development of a wide range of visualization techniques and tools. However, most existing tools are tailored to a specific problem or data type and offer limited customization, making it challenging to optimize visualizations for new analysis tasks or datasets. To address this challenge, we designed Gosling-a grammar for interactive and scalable genomics data visualization. Gosling balances expressiveness for comprehensive multi-scale genomics data visualizations with accessibility for domain scientists. Our accompanying JavaScript toolkit called Gosling.js provides scalable and interactive rendering. Gosling.js is built on top of an existing platform for web-based genomics data visualization to further simplify the visualization of common genomics data formats. We demonstrate the expressiveness of the grammar through a variety of real-world examples. Furthermore, we show how Gosling supports the design of novel genomics visualizations. An online editor and examples of Gosling.js, its source code, and documentation are available at https://gosling.js.org.",
"title": "Gosling: A Grammar-based Toolkit for Scalable and Interactive Genomics Data Visualization",
"normalizedTitle": "Gosling: A Grammar-based Toolkit for Scalable and Interactive Genomics Data Visualization",
"fno": "09557192",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Genomics",
"Bioinformatics",
"Data Visualization",
"Tools",
"Grammar",
"Biological Cells",
"Visualization",
"Genomics",
"Declarative Specification",
"Visualization Grammar"
],
"authors": [
{
"givenName": "Sehi",
"surname": "LYi",
"fullName": "Sehi LYi",
"affiliation": "Harvard Medical School, Boston, MA, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Qianwen",
"surname": "Wang",
"fullName": "Qianwen Wang",
"affiliation": "Harvard Medical School, Boston, MA, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Fritz",
"surname": "Lekschas",
"fullName": "Fritz Lekschas",
"affiliation": "Harvard School of Engineering and Applied Sciences, Boston, MA, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Nils",
"surname": "Gehlenborg",
"fullName": "Nils Gehlenborg",
"affiliation": "Harvard Medical School, Boston, MA, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "140-150",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "trans/tg/2018/08/07999244",
"title": "An Analysis of Automated Visual Analysis Classification: Interactive Visualization Task Inference of Cancer Genomics Domain Experts",
"doi": null,
"abstractUrl": "/journal/tg/2018/08/07999244/13rRUNvgz9Z",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2017/01/07539391",
"title": "Synteny Explorer: An Interactive Visualization Application for Teaching Genome Evolution",
"doi": null,
"abstractUrl": "/journal/tg/2017/01/07539391/13rRUxASuAy",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2018/12/08233127",
"title": "Atom: A Grammar for Unit Visualizations",
"doi": null,
"abstractUrl": "/journal/tg/2018/12/08233127/14H4WLzSYsE",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tc/2019/01/08410020",
"title": "Optimal Binning for Genomics",
"doi": null,
"abstractUrl": "/journal/tc/2019/01/08410020/17D45VsBU46",
"parentPublication": {
"id": "trans/tc",
"title": "IEEE Transactions on Computers",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/itme/2018/7744/0/774400a688",
"title": "A Mobile Tool for Interactive Visualisation of Genomics Data",
"doi": null,
"abstractUrl": "/proceedings-article/itme/2018/774400a688/17D45XdBRSw",
"parentPublication": {
"id": "proceedings/itme/2018/7744/0",
"title": "2018 9th International Conference on Information Technology in Medicine and Education (ITME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iisa/2018/8161/0/08633632",
"title": "Business Management System for Genomics",
"doi": null,
"abstractUrl": "/proceedings-article/iisa/2018/08633632/17D45XwUAKG",
"parentPublication": {
"id": "proceedings/iisa/2018/8161/0",
"title": "2018 9th International Conference on Information, Intelligence, Systems and Applications (IISA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09904451",
"title": "Multi-View Design Patterns and Responsive Visualization for Genomics Data",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09904451/1H1gfVbEsiA",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09908148",
"title": "GenoREC: A Recommendation System for Interactive Genomics Data Visualization",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09908148/1Hbaqe3xebS",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09914804",
"title": "Animated Vega-Lite: Unifying Animation with a Grammar of Interactive Graphics",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09914804/1Hmgc5h7Clq",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2020/9134/0/913400a385",
"title": "InstaCircos: a Web Application for Fast and Interactive Circular Visualization of Large Genomic Data (Work in Progress)",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2020/913400a385/1rSRcelsx5m",
"parentPublication": {
"id": "proceedings/iv/2020/9134/0",
"title": "2020 24th International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552592",
"articleId": "1xic0SUdCNO",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09555227",
"articleId": "1xjR1zzHe6s",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zKXpiDhzJC",
"name": "ttg202201-09557192s1-supp1-3114876.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09557192s1-supp1-3114876.mp4",
"extension": "mp4",
"size": "172 MB",
"__typename": "WebExtraType"
},
{
"id": "1zKXoKFF8R2",
"name": "ttg202201-09557192s1-supp2-3114876.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09557192s1-supp2-3114876.pdf",
"extension": "pdf",
"size": "646 kB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xjR1zzHe6s",
"doi": "10.1109/TVCG.2021.3114810",
"abstract": "Although cancer patients survive years after oncologic therapy, they are plagued with long-lasting or permanent residual symptoms, whose severity, rate of development, and resolution after treatment vary largely between survivors. The analysis and interpretation of symptoms is complicated by their partial co-occurrence, variability across populations and across time, and, in the case of cancers that use radiotherapy, by further symptom dependency on the tumor location and prescribed treatment. We describe THALIS, an environment for visual analysis and knowledge discovery from cancer therapy symptom data, developed in close collaboration with oncology experts. Our approach leverages unsupervised machine learning methodology over cohorts of patients, and, in conjunction with custom visual encodings and interactions, provides context for new patients based on patients with similar diagnostic features and symptom evolution. We evaluate this approach on data collected from a cohort of head and neck cancer patients. Feedback from our clinician collaborators indicates that THALIS supports knowledge discovery beyond the limits of machines or humans alone, and that it serves as a valuable tool in both the clinic and symptom research.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Although cancer patients survive years after oncologic therapy, they are plagued with long-lasting or permanent residual symptoms, whose severity, rate of development, and resolution after treatment vary largely between survivors. The analysis and interpretation of symptoms is complicated by their partial co-occurrence, variability across populations and across time, and, in the case of cancers that use radiotherapy, by further symptom dependency on the tumor location and prescribed treatment. We describe THALIS, an environment for visual analysis and knowledge discovery from cancer therapy symptom data, developed in close collaboration with oncology experts. Our approach leverages unsupervised machine learning methodology over cohorts of patients, and, in conjunction with custom visual encodings and interactions, provides context for new patients based on patients with similar diagnostic features and symptom evolution. We evaluate this approach on data collected from a cohort of head and neck cancer patients. Feedback from our clinician collaborators indicates that THALIS supports knowledge discovery beyond the limits of machines or humans alone, and that it serves as a valuable tool in both the clinic and symptom research.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Although cancer patients survive years after oncologic therapy, they are plagued with long-lasting or permanent residual symptoms, whose severity, rate of development, and resolution after treatment vary largely between survivors. The analysis and interpretation of symptoms is complicated by their partial co-occurrence, variability across populations and across time, and, in the case of cancers that use radiotherapy, by further symptom dependency on the tumor location and prescribed treatment. We describe THALIS, an environment for visual analysis and knowledge discovery from cancer therapy symptom data, developed in close collaboration with oncology experts. Our approach leverages unsupervised machine learning methodology over cohorts of patients, and, in conjunction with custom visual encodings and interactions, provides context for new patients based on patients with similar diagnostic features and symptom evolution. We evaluate this approach on data collected from a cohort of head and neck cancer patients. Feedback from our clinician collaborators indicates that THALIS supports knowledge discovery beyond the limits of machines or humans alone, and that it serves as a valuable tool in both the clinic and symptom research.",
"title": "THALIS: Human-Machine Analysis of Longitudinal Symptoms in Cancer Therapy",
"normalizedTitle": "THALIS: Human-Machine Analysis of Longitudinal Symptoms in Cancer Therapy",
"fno": "09555227",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Cancer",
"Visualization",
"Medical Treatment",
"Data Visualization",
"Encoding",
"Principal Component Analysis",
"Neck",
"Temporal Data",
"Application Motivated Visualization",
"Life Sciences",
"Mixed Initiative Human Machine Analysis"
],
"authors": [
{
"givenName": "Carla",
"surname": "Floricel",
"fullName": "Carla Floricel",
"affiliation": "University of Illinois, Chicago, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Nafiul",
"surname": "Nipu",
"fullName": "Nafiul Nipu",
"affiliation": "University of Illinois, Chicago, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Mikayla",
"surname": "Biggs",
"fullName": "Mikayla Biggs",
"affiliation": "University of Iowa, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Andrew",
"surname": "Wentzel",
"fullName": "Andrew Wentzel",
"affiliation": "University of Illinois, Chicago, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Guadalupe",
"surname": "Canahuate",
"fullName": "Guadalupe Canahuate",
"affiliation": "University of Iowa, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Lisanne",
"surname": "Van Dijk",
"fullName": "Lisanne Van Dijk",
"affiliation": "MD Anderson Cancer Center at the University of Texas, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Abdallah",
"surname": "Mohamed",
"fullName": "Abdallah Mohamed",
"affiliation": "MD Anderson Cancer Center at the University of Texas, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "C.David",
"surname": "Fuller",
"fullName": "C.David Fuller",
"affiliation": "MD Anderson Cancer Center at the University of Texas, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "G.Elisabeta",
"surname": "Marai",
"fullName": "G.Elisabeta Marai",
"affiliation": "University of Illinois, Chicago, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "151-161",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/ichi/2016/6117/0/6117a504",
"title": "Serenity: A Low-Cost and Patient-Guided Mobile Virtual Reality Intervention for Cancer Coping",
"doi": null,
"abstractUrl": "/proceedings-article/ichi/2016/6117a504/12OmNAkWvD4",
"parentPublication": {
"id": "proceedings/ichi/2016/6117/0",
"title": "2016 IEEE International Conference on Healthcare Informatics (ICHI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/itme/2015/8302/0/8302a264",
"title": "The Analysis of Endoscopic-Assisted Neck Minimally Invasive Radical Operation of Thyroid Cancer (Experience of 402 Cases)",
"doi": null,
"abstractUrl": "/proceedings-article/itme/2015/8302a264/12OmNCm7BHY",
"parentPublication": {
"id": "proceedings/itme/2015/8302/0",
"title": "2015 7th International Conference on Information Technology in Medicine and Education (ITME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bmei/2008/3118/2/3118b718",
"title": "Measurements of Radiation-Induced Skin Changes in Breast-Cancer Radiation Therapy Using Ultrasonic Imaging",
"doi": null,
"abstractUrl": "/proceedings-article/bmei/2008/3118b718/12OmNvAAtBf",
"parentPublication": {
"id": "proceedings/bmei/2008/3118/2",
"title": "BioMedical Engineering and Informatics, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wimob/2017/3839/0/08115825",
"title": "Smart-phone based monitoring of cancer related fatigue",
"doi": null,
"abstractUrl": "/proceedings-article/wimob/2017/08115825/12OmNwEJ0EW",
"parentPublication": {
"id": "proceedings/wimob/2017/3839/0",
"title": "2017 IEEE 13th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2014/5669/0/06999169",
"title": "VISWES: A system for finding related vaccinia virus protein sequences in cancer immune therapy",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2014/06999169/12OmNyGtjlN",
"parentPublication": {
"id": "proceedings/bibm/2014/5669/0",
"title": "2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wetice/2011/4410/0/4410a151",
"title": "Comparison of Machine Learning Techniques using the WEKA Environment for Prostate Cancer Therapy Plan",
"doi": null,
"abstractUrl": "/proceedings-article/wetice/2011/4410a151/12OmNyYm2px",
"parentPublication": {
"id": "proceedings/wetice/2011/4410/0",
"title": "2011 IEEE 20th International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/itme/2018/7744/0/774400a217",
"title": "Intensity Modulated Arc Therapy (IMAT) vs. IMRT in Glottic Cancer: A Treatment Planning Comparison on Conventional Linac",
"doi": null,
"abstractUrl": "/proceedings-article/itme/2018/774400a217/17D45WWzW5p",
"parentPublication": {
"id": "proceedings/itme/2018/7744/0",
"title": "2018 9th International Conference on Information Technology in Medicine and Education (ITME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/04/08320386",
"title": "Precision Risk Analysis of Cancer Therapy with Interactive Nomograms and Survival Plots",
"doi": null,
"abstractUrl": "/journal/tg/2019/04/08320386/181W9pIePIs",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/itme/2021/0679/0/067900a446",
"title": "TraditionalChineseMedicine characteristic therapy treats obstinate hiccup",
"doi": null,
"abstractUrl": "/proceedings-article/itme/2021/067900a446/1CATshHvh2E",
"parentPublication": {
"id": "proceedings/itme/2021/0679/0",
"title": "2021 11th International Conference on Information Technology in Medicine and Education (ITME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2020/6215/0/09313509",
"title": "A multi-task learning method for analyzing microbiota as cancer immunotherapy signal",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2020/09313509/1qmg4AVFi80",
"parentPublication": {
"id": "proceedings/bibm/2020/6215/0",
"title": "2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09557192",
"articleId": "1xlw1UFWxDa",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552449",
"articleId": "1xic65iQBoY",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xic65iQBoY",
"doi": "10.1109/TVCG.2021.3114826",
"abstract": "We contribute a deep-learning-based method that assists in designing analytical dashboards for analyzing a data table. Given a data table, data workers usually need to experience a tedious and time-consuming process to select meaningful combinations of data columns for creating charts. This process is further complicated by the needs of creating dashboards composed of multiple views that unveil different perspectives of data. Existing automated approaches for recommending multiple-view visualizations mainly build on manually crafted design rules, producing sub-optimal or irrelevant suggestions. To address this gap, we present a deep learning approach for selecting data columns and recommending multiple charts. More importantly, we integrate the deep learning models into a mixed-initiative system. Our model could make recommendations given optional user-input selections of data columns. The model, in turn, learns from provenance data of authoring logs in an offline manner. We compare our deep learning model with existing methods for visualization recommendation and conduct a user study to evaluate the usefulness of the system.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We contribute a deep-learning-based method that assists in designing analytical dashboards for analyzing a data table. Given a data table, data workers usually need to experience a tedious and time-consuming process to select meaningful combinations of data columns for creating charts. This process is further complicated by the needs of creating dashboards composed of multiple views that unveil different perspectives of data. Existing automated approaches for recommending multiple-view visualizations mainly build on manually crafted design rules, producing sub-optimal or irrelevant suggestions. To address this gap, we present a deep learning approach for selecting data columns and recommending multiple charts. More importantly, we integrate the deep learning models into a mixed-initiative system. Our model could make recommendations given optional user-input selections of data columns. The model, in turn, learns from provenance data of authoring logs in an offline manner. We compare our deep learning model with existing methods for visualization recommendation and conduct a user study to evaluate the usefulness of the system.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We contribute a deep-learning-based method that assists in designing analytical dashboards for analyzing a data table. Given a data table, data workers usually need to experience a tedious and time-consuming process to select meaningful combinations of data columns for creating charts. This process is further complicated by the needs of creating dashboards composed of multiple views that unveil different perspectives of data. Existing automated approaches for recommending multiple-view visualizations mainly build on manually crafted design rules, producing sub-optimal or irrelevant suggestions. To address this gap, we present a deep learning approach for selecting data columns and recommending multiple charts. More importantly, we integrate the deep learning models into a mixed-initiative system. Our model could make recommendations given optional user-input selections of data columns. The model, in turn, learns from provenance data of authoring logs in an offline manner. We compare our deep learning model with existing methods for visualization recommendation and conduct a user study to evaluate the usefulness of the system.",
"title": "MultiVision: Designing Analytical Dashboards with Deep Learning Based Recommendation",
"normalizedTitle": "MultiVision: Designing Analytical Dashboards with Deep Learning Based Recommendation",
"fno": "09552449",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Data Visualisation",
"Interactive Systems",
"Learning Artificial Intelligence",
"Recommender Systems",
"Creating Charts",
"Multiple View Visualizations",
"Manually Crafted Design Rules",
"Deep Learning Approach",
"Data Columns",
"Recommending Multiple Charts",
"Deep Learning Model",
"Optional User Input Selections",
"Provenance Data",
"Visualization Recommendation",
"Designing Analytical Dashboards",
"Based Recommendation",
"Data Table",
"Data Workers",
"Tedious Time Consuming Process",
"Data Visualization",
"Visualization",
"Encoding",
"Deep Learning",
"Tools",
"Measurement",
"Layout",
"Visualization Recommendation",
"Deep Learning",
"Multiple View",
"Dashboard",
"Mixed Initiative",
"Visualization Provenance"
],
"authors": [
{
"givenName": "Aoyu",
"surname": "Wu",
"fullName": "Aoyu Wu",
"affiliation": "Hong Kong University of Science and Technology, Hong Kong",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yun",
"surname": "Wang",
"fullName": "Yun Wang",
"affiliation": "Microsoft Research Area, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Mengyu",
"surname": "Zhou",
"fullName": "Mengyu Zhou",
"affiliation": "Microsoft Research Area, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Xinyi",
"surname": "He",
"fullName": "Xinyi He",
"affiliation": "Microsoft Research Area, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Haidong",
"surname": "Zhang",
"fullName": "Haidong Zhang",
"affiliation": "Microsoft Research Area, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Huamin",
"surname": "Qu",
"fullName": "Huamin Qu",
"affiliation": "Hong Kong University of Science and Technology, Hong Kong",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Dongmei",
"surname": "Zhang",
"fullName": "Dongmei Zhang",
"affiliation": "Microsoft Research Area, United States",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "162-172",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/vahc/2017/3187/0/08387496",
"title": "DataScope: Interactive visual exploratory dashboards for large multidimensional data",
"doi": null,
"abstractUrl": "/proceedings-article/vahc/2017/08387496/12OmNx4Q6FM",
"parentPublication": {
"id": "proceedings/vahc/2017/3187/0",
"title": "2017 IEEE Workshop on Visual Analytics in Healthcare (VAHC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/it/2016/05/mit2016050058",
"title": "Displaying Background Maps in Business Intelligence Dashboards",
"doi": null,
"abstractUrl": "/magazine/it/2016/05/mit2016050058/13rRUx0xPxC",
"parentPublication": {
"id": "mags/it",
"title": "IT Professional",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/so/2013/04/mso2013040046",
"title": "Developer Dashboards: The Need for Qualitative Analytics",
"doi": null,
"abstractUrl": "/magazine/so/2013/04/mso2013040046/13rRUxAAT5z",
"parentPublication": {
"id": "mags/so",
"title": "IEEE Software",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/2016/02/mcg2016020083",
"title": "Lessons Learned from Designing Visualization Dashboards",
"doi": null,
"abstractUrl": "/magazine/cg/2016/02/mcg2016020083/13rRUxBa5zP",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/01/08443395",
"title": "What Do We Talk About When We Talk About Dashboards?",
"doi": null,
"abstractUrl": "/journal/tg/2019/01/08443395/17D45XDIXWb",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09906971",
"title": "DashBot: Insight-Driven Dashboard Generation Based on Deep Reinforcement Learning",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09906971/1H5EWMQX9ZK",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/10057994",
"title": "Dashboard Design Mining and Recommendation",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/10057994/1LbFmG2HHnW",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/09/09035622",
"title": "LADV: Deep Learning Assisted Authoring of Dashboard Visualizations From Images and Sketches",
"doi": null,
"abstractUrl": "/journal/tg/2021/09/09035622/1iaeAO11H6o",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/it/2021/03/09464119",
"title": "Rigorous Data Validation for Accurate Dashboards: Experience From a Higher Education Institution",
"doi": null,
"abstractUrl": "/magazine/it/2021/03/09464119/1uHcqgoeili",
"parentPublication": {
"id": "mags/it",
"title": "IT Professional",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/conisoft/2021/4361/0/436100a034",
"title": "Information Visualization In Adaptable Dashboards For Smart Cities: A Systematic Review",
"doi": null,
"abstractUrl": "/proceedings-article/conisoft/2021/436100a034/1zHIifIcW4w",
"parentPublication": {
"id": "proceedings/conisoft/2021/4361/0",
"title": "2021 9th International Conference in Software Engineering Research and Innovation (CONISOFT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09555227",
"articleId": "1xjR1zzHe6s",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09585700",
"articleId": "1y11cGSPuPC",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBaRp3TMvC",
"name": "ttg202201-09552449s1-supp1-3114826.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552449s1-supp1-3114826.mp4",
"extension": "mp4",
"size": "8.19 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1y11cGSPuPC",
"doi": "10.1109/TVCG.2021.3114856",
"abstract": "Infographic bar charts have been widely adopted for communicating numerical information because of their attractiveness and memorability. However, these infographics are often created manually with general tools, such as PowerPoint and Adobe Illustrator, and merely composed of primitive visual elements, such as text blocks and shapes. With the absence of chart models, updating or reusing these infographics requires tedious and error-prone manual edits. In this paper, we propose a mixed-initiative approach to mitigate this pain point. On one hand, machines are adopted to perform precise and trivial operations, such as mapping numerical values to shape attributes and aligning shapes. On the other hand, we rely on humans to perform subjective and creative tasks, such as changing embellishments or approving the edits made by machines. We encapsulate our technique in a PowerPoint add-in prototype and demonstrate the effectiveness by applying our technique on a diverse set of infographic bar chart examples.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Infographic bar charts have been widely adopted for communicating numerical information because of their attractiveness and memorability. However, these infographics are often created manually with general tools, such as PowerPoint and Adobe Illustrator, and merely composed of primitive visual elements, such as text blocks and shapes. With the absence of chart models, updating or reusing these infographics requires tedious and error-prone manual edits. In this paper, we propose a mixed-initiative approach to mitigate this pain point. On one hand, machines are adopted to perform precise and trivial operations, such as mapping numerical values to shape attributes and aligning shapes. On the other hand, we rely on humans to perform subjective and creative tasks, such as changing embellishments or approving the edits made by machines. We encapsulate our technique in a PowerPoint add-in prototype and demonstrate the effectiveness by applying our technique on a diverse set of infographic bar chart examples.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Infographic bar charts have been widely adopted for communicating numerical information because of their attractiveness and memorability. However, these infographics are often created manually with general tools, such as PowerPoint and Adobe Illustrator, and merely composed of primitive visual elements, such as text blocks and shapes. With the absence of chart models, updating or reusing these infographics requires tedious and error-prone manual edits. In this paper, we propose a mixed-initiative approach to mitigate this pain point. On one hand, machines are adopted to perform precise and trivial operations, such as mapping numerical values to shape attributes and aligning shapes. On the other hand, we rely on humans to perform subjective and creative tasks, such as changing embellishments or approving the edits made by machines. We encapsulate our technique in a PowerPoint add-in prototype and demonstrate the effectiveness by applying our technique on a diverse set of infographic bar chart examples.",
"title": "A Mixed-Initiative Approach to Reusing Infographic Charts",
"normalizedTitle": "A Mixed-Initiative Approach to Reusing Infographic Charts",
"fno": "09585700",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Bars",
"Visualization",
"Tools",
"Shape",
"Data Mining",
"Semantics",
"Image Color Analysis",
"Infographics",
"Reusable Templates",
"Graphic Design",
"Automatic Visualization"
],
"authors": [
{
"givenName": "Weiwei",
"surname": "Cui",
"fullName": "Weiwei Cui",
"affiliation": "Microsoft Research Asia, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jinpeng",
"surname": "Wang",
"fullName": "Jinpeng Wang",
"affiliation": "Meituan, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "He",
"surname": "Huang",
"fullName": "He Huang",
"affiliation": "Microsoft Research Asia, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yun",
"surname": "Wang",
"fullName": "Yun Wang",
"affiliation": "Microsoft Research Asia, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Chin-Yew",
"surname": "Lin",
"fullName": "Chin-Yew Lin",
"affiliation": "Microsoft Research Asia, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Haidong",
"surname": "Zhang",
"fullName": "Haidong Zhang",
"affiliation": "Microsoft Research Asia, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Dongmei",
"surname": "Zhang",
"fullName": "Dongmei Zhang",
"affiliation": "Microsoft Research Asia, China",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "173-183",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/icpr/1994/6270/2/00576979",
"title": "An extended-shadow-code based approach for off-line signature verification. I. Evaluation of the bar mask definition",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/1994/00576979/12OmNyQ7FNm",
"parentPublication": {
"id": "proceedings/icpr/1994/6270/2",
"title": "Proceedings of 12th International Conference on Pattern Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2018/03/07845717",
"title": "Converting Basic D3 Charts into Reusable Style Templates",
"doi": null,
"abstractUrl": "/journal/tg/2018/03/07845717/13rRUxYINfm",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/01/08440833",
"title": "SmartCues: A Multitouch Query Approach for Details-on-Demand through Dynamically Computed Overlays",
"doi": null,
"abstractUrl": "/journal/tg/2019/01/08440833/17D45Vw15wL",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2020/01/08807355",
"title": "ShapeWordle: Tailoring Wordles using Shape-aware Archimedean Spirals",
"doi": null,
"abstractUrl": "/journal/tg/2020/01/08807355/1cG6a6b0eys",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv-2/2019/2850/0/285000a042",
"title": "An Interactive Method for Visualising Physical Activity in Parks",
"doi": null,
"abstractUrl": "/proceedings-article/iv-2/2019/285000a042/1cMEPkhBBKw",
"parentPublication": {
"id": "proceedings/iv-2/2019/2850/0",
"title": "2019 23rd International Conference in Information Visualization – Part II",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vis/2019/4941/0/08933569",
"title": "Toward Interface Defaults for Vague Modifiers in Natural Language Interfaces for Visual Analysis",
"doi": null,
"abstractUrl": "/proceedings-article/vis/2019/08933569/1fTgHCV29i0",
"parentPublication": {
"id": "proceedings/vis/2019/4941/0",
"title": "2019 IEEE Visualization Conference (VIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/02/09222351",
"title": "Palettailor: Discriminable Colorization for Categorical Data",
"doi": null,
"abstractUrl": "/journal/tg/2021/02/09222351/1nTq353vBNS",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pacificvis/2021/3931/0/393100a031",
"title": "Parsing and Summarizing Infographics with Synthetically Trained Icon Detection",
"doi": null,
"abstractUrl": "/proceedings-article/pacificvis/2021/393100a031/1tTts9CdeyQ",
"parentPublication": {
"id": "proceedings/pacificvis/2021/3931/0",
"title": "2021 IEEE 14th Pacific Visualization Symposium (PacificVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2021/8808/0/09412507",
"title": "Anime Sketch Colorization by Component-based Matching using Deep Appearance Features and Graph Representation",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2021/09412507/1tmhNNPsnrG",
"parentPublication": {
"id": "proceedings/icpr/2021/8808/0",
"title": "2020 25th International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/01/09552208",
"title": "Visual Arrangements of Bar Charts Influence Comparisons in Viewer Takeaways",
"doi": null,
"abstractUrl": "/journal/tg/2022/01/09552208/1xibWU97C8w",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552449",
"articleId": "1xic65iQBoY",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552930",
"articleId": "1xic4JnxG2k",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBaBdOFJo4",
"name": "ttg202201-09585700s1-supp1-3114856.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09585700s1-supp1-3114856.mp4",
"extension": "mp4",
"size": "17.2 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xic4JnxG2k",
"doi": "10.1109/TVCG.2021.3114802",
"abstract": "Charts go hand in hand with text to communicate complex data and are widely adopted in news articles, online blogs, and academic papers. They provide graphical summaries of the data, while text explains the message and context. However, synthesizing information across text and charts is difficult; it requires readers to frequently shift their attention. We investigated ways to support the tight coupling of text and charts in data documents. To understand their interplay, we analyzed the design space of chart-text references through news articles and scientific papers. Informed by the analysis, we developed a mixed-initiative interface enabling users to construct interactive references between text and charts. It leverages natural language processing to automatically suggest references as well as allows users to manually construct other references effortlessly. A user study complemented with algorithmic evaluation of the system suggests that the interface provides an effective way to compose interactive data documents.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Charts go hand in hand with text to communicate complex data and are widely adopted in news articles, online blogs, and academic papers. They provide graphical summaries of the data, while text explains the message and context. However, synthesizing information across text and charts is difficult; it requires readers to frequently shift their attention. We investigated ways to support the tight coupling of text and charts in data documents. To understand their interplay, we analyzed the design space of chart-text references through news articles and scientific papers. Informed by the analysis, we developed a mixed-initiative interface enabling users to construct interactive references between text and charts. It leverages natural language processing to automatically suggest references as well as allows users to manually construct other references effortlessly. A user study complemented with algorithmic evaluation of the system suggests that the interface provides an effective way to compose interactive data documents.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Charts go hand in hand with text to communicate complex data and are widely adopted in news articles, online blogs, and academic papers. They provide graphical summaries of the data, while text explains the message and context. However, synthesizing information across text and charts is difficult; it requires readers to frequently shift their attention. We investigated ways to support the tight coupling of text and charts in data documents. To understand their interplay, we analyzed the design space of chart-text references through news articles and scientific papers. Informed by the analysis, we developed a mixed-initiative interface enabling users to construct interactive references between text and charts. It leverages natural language processing to automatically suggest references as well as allows users to manually construct other references effortlessly. A user study complemented with algorithmic evaluation of the system suggests that the interface provides an effective way to compose interactive data documents.",
"title": "Kori: Interactive Synthesis of Text and Charts in Data Documents",
"normalizedTitle": "Kori: Interactive Synthesis of Text and Charts in Data Documents",
"fno": "09552930",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Natural Language Processing",
"Text Analysis",
"User Interfaces",
"Academic Papers",
"Chart Text References",
"Charts",
"Complex Data",
"Interactive Data Documents",
"Interactive Synthesis",
"Kori",
"Natural Language Processing",
"News Articles",
"Data Visualization",
"Visualization",
"Tools",
"Programming",
"Bars",
"Syntactics",
"Natural Language Processing",
"Data Driven Storytelling",
"Interaction Design",
"Authoring",
"Visualization Text Linking",
"Mixed Initiative Interface",
"Interactive Documents"
],
"authors": [
{
"givenName": "Shahid",
"surname": "Latif",
"fullName": "Shahid Latif",
"affiliation": "University of Duisburg-Essen, Germany",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Zheng",
"surname": "Zhou",
"fullName": "Zheng Zhou",
"affiliation": "Boston College, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yoon",
"surname": "Kim",
"fullName": "Yoon Kim",
"affiliation": "Harvard University, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Fabian",
"surname": "Beck",
"fullName": "Fabian Beck",
"affiliation": "University of Duisburg-Essen, Germany",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Nam Wook",
"surname": "Kim",
"fullName": "Nam Wook Kim",
"affiliation": "Boston College, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "184-194",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/iv/2017/0831/0/0831a096",
"title": "Microtext Line Charts",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2017/0831a096/12OmNAqkSCW",
"parentPublication": {
"id": "proceedings/iv/2017/0831/0",
"title": "2017 21st International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aiccsa/2013/0792/0/06616467",
"title": "Identifying temporal relations between main events in new articles",
"doi": null,
"abstractUrl": "/proceedings-article/aiccsa/2013/06616467/12OmNvjQ8WN",
"parentPublication": {
"id": "proceedings/aiccsa/2013/0792/0",
"title": "2013 ACS International Conference on Computer Systems and Applications (AICCSA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/caia/1991/2135/1/00120841",
"title": "Extracting company names from text",
"doi": null,
"abstractUrl": "/proceedings-article/caia/1991/00120841/12OmNzcxZlp",
"parentPublication": {
"id": "proceedings/caia/1991/2135/1",
"title": "Proceedings The Seventh IEEE Conference on Artificial Intelligence Application",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2018/01/08017611",
"title": "Blinded with Science or Informed by Charts? A Replication Study",
"doi": null,
"abstractUrl": "/journal/tg/2018/01/08017611/13rRUxAAT7J",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2016/01/07192669",
"title": "TimeLineCurator: Interactive Authoring of Visual Timelines from Unstructured Text",
"doi": null,
"abstractUrl": "/journal/tg/2016/01/07192669/13rRUxjQyvn",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sibgrapi/2018/9264/0/926400a142",
"title": "Extracting Visual Encodings from Map Chart Images with Color-Encoded Scalar Values",
"doi": null,
"abstractUrl": "/proceedings-article/sibgrapi/2018/926400a142/17D45WaTkiB",
"parentPublication": {
"id": "proceedings/sibgrapi/2018/9264/0",
"title": "2018 31st SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icnlp/2022/9544/0/954400a385",
"title": "Investigating Text Complexity of Reading in National Matriculation English Test",
"doi": null,
"abstractUrl": "/proceedings-article/icnlp/2022/954400a385/1GNtszOPwfS",
"parentPublication": {
"id": "proceedings/icnlp/2022/9544/0",
"title": "2022 4th International Conference on Natural Language Processing (ICNLP)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09904452",
"title": "Striking a Balance: Reader Takeaways and Preferences when Integrating Text and Charts",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09904452/1H1gordOnfy",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2019/2838/0/283800a151",
"title": "The Cost of Pie Charts",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2019/283800a151/1cMFcqwGM5q",
"parentPublication": {
"id": "proceedings/iv/2019/2838/0",
"title": "2019 23rd International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2020/2903/0/09101527",
"title": "Crowdsourcing-based Data Extraction from Visualization Charts",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2020/09101527/1kaMJ95VHQk",
"parentPublication": {
"id": "proceedings/icde/2020/2903/0",
"title": "2020 IEEE 36th International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09585700",
"articleId": "1y11cGSPuPC",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552844",
"articleId": "1xic3q426Os",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBaP58HDxu",
"name": "ttg202201-09552930s1-tvcg-3114802-mm.zip",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552930s1-tvcg-3114802-mm.zip",
"extension": "zip",
"size": "27.4 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xic3q426Os",
"doi": "10.1109/TVCG.2021.3114863",
"abstract": "Visualization recommendation or automatic visualization generation can significantly lower the barriers for general users to rapidly create effective data visualizations, especially for those users without a background in data visualizations. However, existing rule-based approaches require tedious manual specifications of visualization rules by visualization experts. Other machine learning-based approaches often work like black-box and are difficult to understand why a specific visualization is recommended, limiting the wider adoption of these approaches. This paper fills the gap by presenting KG4Vis, a knowledge graph (KG)-based approach for visualization recommendation. It does not require manual specifications of visualization rules and can also guarantee good explainability. Specifically, we propose a framework for building knowledge graphs, consisting of three types of entities (i.e., data features, data columns and visualization design choices) and the relations between them, to model the mapping rules between data and effective visualizations. A TransE-based embedding technique is employed to learn the embeddings of both entities and relations of the knowledge graph from existing dataset-visualization pairs. Such embeddings intrinsically model the desirable visualization rules. Then, given a new dataset, effective visualizations can be inferred from the knowledge graph with semantically meaningful rules. We conducted extensive evaluations to assess the proposed approach, including quantitative comparisons, case studies and expert interviews. The results demonstrate the effectiveness of our approach.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Visualization recommendation or automatic visualization generation can significantly lower the barriers for general users to rapidly create effective data visualizations, especially for those users without a background in data visualizations. However, existing rule-based approaches require tedious manual specifications of visualization rules by visualization experts. Other machine learning-based approaches often work like black-box and are difficult to understand why a specific visualization is recommended, limiting the wider adoption of these approaches. This paper fills the gap by presenting KG4Vis, a knowledge graph (KG)-based approach for visualization recommendation. It does not require manual specifications of visualization rules and can also guarantee good explainability. Specifically, we propose a framework for building knowledge graphs, consisting of three types of entities (i.e., data features, data columns and visualization design choices) and the relations between them, to model the mapping rules between data and effective visualizations. A TransE-based embedding technique is employed to learn the embeddings of both entities and relations of the knowledge graph from existing dataset-visualization pairs. Such embeddings intrinsically model the desirable visualization rules. Then, given a new dataset, effective visualizations can be inferred from the knowledge graph with semantically meaningful rules. We conducted extensive evaluations to assess the proposed approach, including quantitative comparisons, case studies and expert interviews. The results demonstrate the effectiveness of our approach.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Visualization recommendation or automatic visualization generation can significantly lower the barriers for general users to rapidly create effective data visualizations, especially for those users without a background in data visualizations. However, existing rule-based approaches require tedious manual specifications of visualization rules by visualization experts. Other machine learning-based approaches often work like black-box and are difficult to understand why a specific visualization is recommended, limiting the wider adoption of these approaches. This paper fills the gap by presenting KG4Vis, a knowledge graph (KG)-based approach for visualization recommendation. It does not require manual specifications of visualization rules and can also guarantee good explainability. Specifically, we propose a framework for building knowledge graphs, consisting of three types of entities (i.e., data features, data columns and visualization design choices) and the relations between them, to model the mapping rules between data and effective visualizations. A TransE-based embedding technique is employed to learn the embeddings of both entities and relations of the knowledge graph from existing dataset-visualization pairs. Such embeddings intrinsically model the desirable visualization rules. Then, given a new dataset, effective visualizations can be inferred from the knowledge graph with semantically meaningful rules. We conducted extensive evaluations to assess the proposed approach, including quantitative comparisons, case studies and expert interviews. The results demonstrate the effectiveness of our approach.",
"title": "<italic>KG4Vis:</italic> A Knowledge Graph-Based Approach for Visualization Recommendation",
"normalizedTitle": "KG4Vis: A Knowledge Graph-Based Approach for Visualization Recommendation",
"fno": "09552844",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Data Visualisation",
"Graph Theory",
"Learning Artificial Intelligence",
"Automatic Visualization Generation",
"Effective Data Visualizations",
"Existing Rule Based Approaches",
"Tedious Manual Specifications",
"Visualization Experts",
"Machine Learning Based Approaches",
"Specific Visualization",
"Knowledge Graph Based Approach",
"Visualization Recommendation",
"Visualization Design Choices",
"Effective Visualizations",
"Trans E Based",
"Dataset Visualization Pairs",
"Desirable Visualization Rules",
"Data Visualization",
"Feature Extraction",
"Tools",
"Manuals",
"Data Models",
"Visualization",
"Interviews",
"Data Visualization",
"Visualization Recommendation",
"Knowledge Graph"
],
"authors": [
{
"givenName": "Haotian",
"surname": "Li",
"fullName": "Haotian Li",
"affiliation": "Hong Kong University of Science and Technology and Singapore Management University, Hong Kong",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yong",
"surname": "Wang",
"fullName": "Yong Wang",
"affiliation": "Singapore Management University, Singapore",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Songheng",
"surname": "Zhang",
"fullName": "Songheng Zhang",
"affiliation": "Singapore Management University, Singapore",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yangqiu",
"surname": "Song",
"fullName": "Yangqiu Song",
"affiliation": "Hong Kong University of Science and Technology, Hong Kong",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Huamin",
"surname": "Qu",
"fullName": "Huamin Qu",
"affiliation": "Hong Kong University of Science and Technology, Hong Kong",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "195-205",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/hicss/2012/4525/0/4525e001",
"title": "Dynamic Knowledge Mapping: A Visualization Approach for Knowledge Management Systems",
"doi": null,
"abstractUrl": "/proceedings-article/hicss/2012/4525e001/12OmNASraz1",
"parentPublication": {
"id": "proceedings/hicss/2012/4525/0",
"title": "2012 45th Hawaii International Conference on System Sciences",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2004/2177/0/21770519",
"title": "Learning from Architects: The Difference between Knowledge Visualization and Information Visualization",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2004/21770519/12OmNx9nGLN",
"parentPublication": {
"id": "proceedings/iv/2004/2177/0",
"title": "Proceedings. Eighth International Conference on Information Visualisation, 2004. IV 2004.",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icicta/2008/3357/2/3357c767",
"title": "The Application of Visualization Technology on Knowledge Management",
"doi": null,
"abstractUrl": "/proceedings-article/icicta/2008/3357c767/12OmNzFv4hI",
"parentPublication": {
"id": "icicta/2008/3357/2",
"title": "Intelligent Computation Technology and Automation, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2018/5520/0/552000a101",
"title": "DeepEye: Towards Automatic Data Visualization",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2018/552000a101/14Fq0VI6tcV",
"parentPublication": {
"id": "proceedings/icde/2018/5520/0",
"title": "2018 IEEE 34th International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/01/08440831",
"title": "<italic>KnowledgePearls</italic>: Provenance-Based Visualization Retrieval",
"doi": null,
"abstractUrl": "/journal/tg/2019/01/08440831/17D45Wc1ILJ",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/01/08444072",
"title": "Narvis: Authoring Narrative Slideshows for Introducing Data Visualization Designs",
"doi": null,
"abstractUrl": "/journal/tg/2019/01/08444072/17D45WnnFX7",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09903511",
"title": "Supporting Expressive and Faithful Pictorial Visualization Design with Visual Style Transfer",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09903511/1GZokWw73mo",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09908148",
"title": "GenoREC: A Recommendation System for Interactive Genomics Data Visualization",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09908148/1Hbaqe3xebS",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/5555/01/10078374",
"title": "<italic>DiffSeer</italic>: Difference-Based Dynamic Weighted Graph Visualization",
"doi": null,
"abstractUrl": "/magazine/cg/5555/01/10078374/1LINrNziL28",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/01/09552878",
"title": "VizLinter: A Linter and Fixer Framework for Data Visualization",
"doi": null,
"abstractUrl": "/journal/tg/2022/01/09552878/1xic0oVyd5m",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552930",
"articleId": "1xic4JnxG2k",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552878",
"articleId": "1xic0oVyd5m",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xic0oVyd5m",
"doi": "10.1109/TVCG.2021.3114804",
"abstract": "Despite the rising popularity of automated visualization tools, existing systems tend to provide direct results which do not always fit the input data or meet visualization requirements. Therefore, additional specification adjustments are still required in real-world use cases. However, manual adjustments are difficult since most users do not necessarily possess adequate skills or visualization knowledge. Even experienced users might create imperfect visualizations that involve chart construction errors. We present a framework, VizLinter, to help users detect flaws and rectify already-built but defective visualizations. The framework consists of two components, (1) a visualization linter, which applies well-recognized principles to inspect the legitimacy of rendered visualizations, and (2) a visualization fixer, which automatically corrects the detected violations according to the linter. We implement the framework into an online editor prototype based on Vega-Lite specifications. To further evaluate the system, we conduct an in-lab user study. The results prove its effectiveness and efficiency in identifying and fixing errors for data visualizations.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Despite the rising popularity of automated visualization tools, existing systems tend to provide direct results which do not always fit the input data or meet visualization requirements. Therefore, additional specification adjustments are still required in real-world use cases. However, manual adjustments are difficult since most users do not necessarily possess adequate skills or visualization knowledge. Even experienced users might create imperfect visualizations that involve chart construction errors. We present a framework, VizLinter, to help users detect flaws and rectify already-built but defective visualizations. The framework consists of two components, (1) a visualization linter, which applies well-recognized principles to inspect the legitimacy of rendered visualizations, and (2) a visualization fixer, which automatically corrects the detected violations according to the linter. We implement the framework into an online editor prototype based on Vega-Lite specifications. To further evaluate the system, we conduct an in-lab user study. The results prove its effectiveness and efficiency in identifying and fixing errors for data visualizations.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Despite the rising popularity of automated visualization tools, existing systems tend to provide direct results which do not always fit the input data or meet visualization requirements. Therefore, additional specification adjustments are still required in real-world use cases. However, manual adjustments are difficult since most users do not necessarily possess adequate skills or visualization knowledge. Even experienced users might create imperfect visualizations that involve chart construction errors. We present a framework, VizLinter, to help users detect flaws and rectify already-built but defective visualizations. The framework consists of two components, (1) a visualization linter, which applies well-recognized principles to inspect the legitimacy of rendered visualizations, and (2) a visualization fixer, which automatically corrects the detected violations according to the linter. We implement the framework into an online editor prototype based on Vega-Lite specifications. To further evaluate the system, we conduct an in-lab user study. The results prove its effectiveness and efficiency in identifying and fixing errors for data visualizations.",
"title": "VizLinter: A Linter and Fixer Framework for Data Visualization",
"normalizedTitle": "VizLinter: A Linter and Fixer Framework for Data Visualization",
"fno": "09552878",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Data Visualisation",
"Rendering Computer Graphics",
"Visualization Linter",
"Rendering",
"Visualization Fixer",
"Data Visualization",
"Viz Linter",
"Fixer Framework",
"Chart Construction Errors",
"Linter Framework",
"Online Editor Prototype",
"Vega Lite Specifications",
"Data Visualization",
"Encoding",
"Visualization",
"Optimization",
"Tools",
"Programming",
"Codes",
"Visualization Linting",
"Automated Visualization Design",
"Visualization Optimization"
],
"authors": [
{
"givenName": "Qing",
"surname": "Chen",
"fullName": "Qing Chen",
"affiliation": "Intelligent Big Data Visualization Lab at Tongji University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Fuling",
"surname": "Sun",
"fullName": "Fuling Sun",
"affiliation": "Intelligent Big Data Visualization Lab at Tongji University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Xinyue",
"surname": "Xu",
"fullName": "Xinyue Xu",
"affiliation": "Intelligent Big Data Visualization Lab at Tongji University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Zui",
"surname": "Chen",
"fullName": "Zui Chen",
"affiliation": "Intelligent Big Data Visualization Lab at Tongji University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jiazhe",
"surname": "Wang",
"fullName": "Jiazhe Wang",
"affiliation": "Ant Group, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Nan",
"surname": "Cao",
"fullName": "Nan Cao",
"affiliation": "Intelligent Big Data Visualization Lab at Tongji University, China",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "206-216",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "trans/tg/2010/06/ttg2010061164",
"title": "behaviorism: a framework for dynamic data visualization",
"doi": null,
"abstractUrl": "/journal/tg/2010/06/ttg2010061164/13rRUEgs2to",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2013/12/ttg2013122406",
"title": "A Deeper Understanding of Sequence in Narrative Visualization",
"doi": null,
"abstractUrl": "/journal/tg/2013/12/ttg2013122406/13rRUwIF6l7",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/01/08444072",
"title": "Narvis: Authoring Narrative Slideshows for Introducing Data Visualization Designs",
"doi": null,
"abstractUrl": "/journal/tg/2019/01/08444072/17D45WnnFX7",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vis/2022/8812/0/881200a016",
"title": "Streamlining Visualization Authoring in D3 Through User-Driven Templates",
"doi": null,
"abstractUrl": "/proceedings-article/vis/2022/881200a016/1J6heEO48bS",
"parentPublication": {
"id": "proceedings/vis/2022/8812/0",
"title": "2022 IEEE Visualization and Visual Analytics (VIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/re/2019/3912/0/391200a109",
"title": "Visualization Requirements for Business Intelligence Analytics: A Goal-Based, Iterative Framework",
"doi": null,
"abstractUrl": "/proceedings-article/re/2019/391200a109/1fHlvWvStdC",
"parentPublication": {
"id": "proceedings/re/2019/3912/0",
"title": "2019 IEEE 27th International Requirements Engineering Conference (RE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vis/2019/4941/0/08933751",
"title": "Learning Vis Tools: Teaching Data Visualization Tutorials",
"doi": null,
"abstractUrl": "/proceedings-article/vis/2019/08933751/1fTgJc2YdMI",
"parentPublication": {
"id": "proceedings/vis/2019/4941/0",
"title": "2019 IEEE Visualization Conference (VIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/02/09222091",
"title": "StructGraphics: Flexible Visualization Design through Data-Agnostic and Reusable Graphical Structures",
"doi": null,
"abstractUrl": "/journal/tg/2021/02/09222091/1nTroDgoFeo",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cs/2021/02/09391750",
"title": "Interactive Data Visualization in Jupyter Notebooks",
"doi": null,
"abstractUrl": "/magazine/cs/2021/02/09391750/1sq7sW0pjWM",
"parentPublication": {
"id": "mags/cs",
"title": "Computing in Science & Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/01/09552844",
"title": "<italic>KG4Vis:</italic> A Knowledge Graph-Based Approach for Visualization Recommendation",
"doi": null,
"abstractUrl": "/journal/tg/2022/01/09552844/1xic3q426Os",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/01/09557192",
"title": "Gosling: A Grammar-based Toolkit for Scalable and Interactive Genomics Data Visualization",
"doi": null,
"abstractUrl": "/journal/tg/2022/01/09557192/1xlw1UFWxDa",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552844",
"articleId": "1xic3q426Os",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09617561",
"articleId": "1yA76vDzhhC",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zHDF1eMR4Q",
"name": "ttg202201-09552878s1-supp1-3114804.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552878s1-supp1-3114804.mp4",
"extension": "mp4",
"size": "7.69 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1yA76vDzhhC",
"doi": "10.1109/TVCG.2021.3114848",
"abstract": "Supporting the translation from natural language (NL) query to visualization (NL2VIS) can simplify the creation of data visualizations because if successful, anyone can generate visualizations by their natural language from the tabular data. The state-of-the-art NL2VIS approaches (<italic>e.g.</italic>, NL4DV and FlowSense) are based on semantic parsers and heuristic algorithms, which are not end-to-end and are not designed for supporting (possibly) complex data transformations. Deep neural network powered neural machine translation models have made great strides in many machine translation tasks, which suggests that they might be viable for NL2VIS as well. In this paper, we present <bold>ncNet</bold>, a Transformer-based sequence-to-sequence model for supporting NL2VIS, with several novel visualization-aware optimizations, including using attention-forcing to optimize the learning process, and visualization-aware rendering to produce better visualization results. To enhance the capability of machine to comprehend natural language queries, <bold>ncNet</bold> is also designed to take an optional chart template (<italic>e.g.</italic>, a pie chart or a scatter plot) as an additional input, where the chart template will be served as a constraint to limit what could be visualized. We conducted both quantitative evaluation and user study, showing that <bold>ncNet</bold> achieves good accuracy in the <bold>nvBench</bold> benchmark and is easy-to-use.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Supporting the translation from natural language (NL) query to visualization (NL2VIS) can simplify the creation of data visualizations because if successful, anyone can generate visualizations by their natural language from the tabular data. The state-of-the-art NL2VIS approaches (<italic>e.g.</italic>, NL4DV and FlowSense) are based on semantic parsers and heuristic algorithms, which are not end-to-end and are not designed for supporting (possibly) complex data transformations. Deep neural network powered neural machine translation models have made great strides in many machine translation tasks, which suggests that they might be viable for NL2VIS as well. In this paper, we present <bold>ncNet</bold>, a Transformer-based sequence-to-sequence model for supporting NL2VIS, with several novel visualization-aware optimizations, including using attention-forcing to optimize the learning process, and visualization-aware rendering to produce better visualization results. To enhance the capability of machine to comprehend natural language queries, <bold>ncNet</bold> is also designed to take an optional chart template (<italic>e.g.</italic>, a pie chart or a scatter plot) as an additional input, where the chart template will be served as a constraint to limit what could be visualized. We conducted both quantitative evaluation and user study, showing that <bold>ncNet</bold> achieves good accuracy in the <bold>nvBench</bold> benchmark and is easy-to-use.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Supporting the translation from natural language (NL) query to visualization (NL2VIS) can simplify the creation of data visualizations because if successful, anyone can generate visualizations by their natural language from the tabular data. The state-of-the-art NL2VIS approaches (e.g., NL4DV and FlowSense) are based on semantic parsers and heuristic algorithms, which are not end-to-end and are not designed for supporting (possibly) complex data transformations. Deep neural network powered neural machine translation models have made great strides in many machine translation tasks, which suggests that they might be viable for NL2VIS as well. In this paper, we present ncNet, a Transformer-based sequence-to-sequence model for supporting NL2VIS, with several novel visualization-aware optimizations, including using attention-forcing to optimize the learning process, and visualization-aware rendering to produce better visualization results. To enhance the capability of machine to comprehend natural language queries, ncNet is also designed to take an optional chart template (e.g., a pie chart or a scatter plot) as an additional input, where the chart template will be served as a constraint to limit what could be visualized. We conducted both quantitative evaluation and user study, showing that ncNet achieves good accuracy in the nvBench benchmark and is easy-to-use.",
"title": "Natural Language to Visualization by Neural Machine Translation",
"normalizedTitle": "Natural Language to Visualization by Neural Machine Translation",
"fno": "09617561",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Charts",
"Data Visualisation",
"Grammars",
"Language Translation",
"Learning Artificial Intelligence",
"Natural Language Processing",
"Neural Nets",
"Rendering Computer Graphics",
"Natural Language Query",
"Data Visualizations",
"Tabular Data",
"State Of The Art NL 2 VIS Approaches",
"Supporting Complex Data Transformations",
"Neural Network",
"Neural Machine Translation Models",
"Machine Translation Tasks",
"Transformer Based Sequence To Sequence Model",
"Novel Visualization Aware Optimizations",
"Visualization Aware Rendering",
"Visualization Results",
"Data Visualization",
"Natural Languages",
"Bars",
"Deep Learning",
"Machine Translation",
"Visualization",
"Transformers",
"Natural Language Interface",
"Data Visualization",
"Neural Machine Translation",
"Chart Template"
],
"authors": [
{
"givenName": "Yuyu",
"surname": "Luo",
"fullName": "Yuyu Luo",
"affiliation": "Department of Computer Science, Tsinghua University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Nan",
"surname": "Tang",
"fullName": "Nan Tang",
"affiliation": "QCRI, Hamad Bin Khalifa University, Qatar",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Guoliang",
"surname": "Li",
"fullName": "Guoliang Li",
"affiliation": "Department of Computer Science, Tsinghua University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jiawei",
"surname": "Tang",
"fullName": "Jiawei Tang",
"affiliation": "American School of Doha, Doha, Qatar",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Chengliang",
"surname": "Chai",
"fullName": "Chengliang Chai",
"affiliation": "Department of Computer Science, Tsinghua University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Xuedi",
"surname": "Qin",
"fullName": "Xuedi Qin",
"affiliation": "Department of Computer Science, Tsinghua University, China",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "217-226",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/dexa/2000/0680/0/06800143",
"title": "Dialogue Machine Translation System Using Multiple Translation Processors",
"doi": null,
"abstractUrl": "/proceedings-article/dexa/2000/06800143/12OmNvoFjOd",
"parentPublication": {
"id": "proceedings/dexa/2000/0680/0",
"title": "Proceedings 11th International Workshop on Database and Expert Systems Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cisis/2011/4373/0/4373a310",
"title": "UVDict - A Machine Translation Dictionary for Vietnamese Language in UNL System",
"doi": null,
"abstractUrl": "/proceedings-article/cisis/2011/4373a310/12OmNxveNKf",
"parentPublication": {
"id": "proceedings/cisis/2011/4373/0",
"title": "2011 International Conference on Complex, Intelligent, and Software Intensive Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2015/06/07018997",
"title": "Query2Question: Translating Visualization Interaction into Natural Language",
"doi": null,
"abstractUrl": "/journal/tg/2015/06/07018997/13rRUy0HYRr",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmcce/2018/8481/0/848100a506",
"title": "On Application of Natural Language Processing in Machine Translation",
"doi": null,
"abstractUrl": "/proceedings-article/icmcce/2018/848100a506/17D45Wt3Exk",
"parentPublication": {
"id": "proceedings/icmcce/2018/8481/0",
"title": "2018 3rd International Conference on Mechanical, Control and Computer Engineering (ICMCCE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2023/03/09792411",
"title": "Video Pivoting Unsupervised Multi-Modal Machine Translation",
"doi": null,
"abstractUrl": "/journal/tp/2023/03/09792411/1E5LC566SiY",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2022/6946/0/694600f206",
"title": "VALHALLA: Visual Hallucination for Machine Translation",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600f206/1H0MY8bjU8o",
"parentPublication": {
"id": "proceedings/cvpr/2022/6946/0",
"title": "2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09912366",
"title": "Towards Natural Language-Based Visualization Authoring",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09912366/1HeiWkRN3tC",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ecnlpir/2022/7382/0/738200a010",
"title": "Machine Translation Technology Based on Natural Language Processing",
"doi": null,
"abstractUrl": "/proceedings-article/ecnlpir/2022/738200a010/1KMQ3TrehDG",
"parentPublication": {
"id": "proceedings/ecnlpir/2022/7382/0",
"title": "2022 European Conference on Natural Language Processing and Information Retrieval (ECNLPIR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2022/01/09039632",
"title": "Steerable Self-Driving Data Visualization",
"doi": null,
"abstractUrl": "/journal/tk/2022/01/09039632/1igS2v9G6cw",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/ai/2022/04/09612034",
"title": "Ignorance is Bliss: Exploring Defenses Against Invariance-Based Attacks on Neural Machine Translation Systems",
"doi": null,
"abstractUrl": "/journal/ai/2022/04/09612034/1yrDaVPCDew",
"parentPublication": {
"id": "trans/ai",
"title": "IEEE Transactions on Artificial Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552878",
"articleId": "1xic0oVyd5m",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552241",
"articleId": "1xic6RdmNC8",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xic6RdmNC8",
"doi": "10.1109/TVCG.2021.3114851",
"abstract": "Significant work has been done towards deep learning (DL) models for automatic lung and lesion segmentation and classification of COVID-19 on chest CT data. However, comprehensive visualization systems focused on supporting the dual visual+DL diagnosis of COVID-19 are non-existent. We present <italic>COVID-view</italic>, a visualization application specially tailored for radiologists to diagnose COVID-19 from chest CT data. The system incorporates a complete pipeline of automatic lungs segmentation, localization/isolation of lung abnormalities, followed by visualization, visual and DL analysis, and measurement/quantification tools. Our system combines the traditional 2D workflow of radiologists with newer 2D and 3D visualization techniques with DL support for a more comprehensive diagnosis. <italic>COVID-view</italic> incorporates a novel DL model for classifying the patients into positive/negative COVID-19 cases, which acts as a reading aid for the radiologist using <italic>COVID-view</italic> and provides the attention heatmap as an explainable DL for the model output. We designed and evaluated <italic>COVID-view</italic> through suggestions, close feedback and conducting case studies of real-world patient data by expert radiologists who have substantial experience diagnosing chest CT scans for COVID-19, pulmonary embolism, and other forms of lung infections. We present requirements and task analysis for the diagnosis of COVID-19 that motivate our design choices and results in a practical system which is capable of handling real-world patient cases.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Significant work has been done towards deep learning (DL) models for automatic lung and lesion segmentation and classification of COVID-19 on chest CT data. However, comprehensive visualization systems focused on supporting the dual visual+DL diagnosis of COVID-19 are non-existent. We present <italic>COVID-view</italic>, a visualization application specially tailored for radiologists to diagnose COVID-19 from chest CT data. The system incorporates a complete pipeline of automatic lungs segmentation, localization/isolation of lung abnormalities, followed by visualization, visual and DL analysis, and measurement/quantification tools. Our system combines the traditional 2D workflow of radiologists with newer 2D and 3D visualization techniques with DL support for a more comprehensive diagnosis. <italic>COVID-view</italic> incorporates a novel DL model for classifying the patients into positive/negative COVID-19 cases, which acts as a reading aid for the radiologist using <italic>COVID-view</italic> and provides the attention heatmap as an explainable DL for the model output. We designed and evaluated <italic>COVID-view</italic> through suggestions, close feedback and conducting case studies of real-world patient data by expert radiologists who have substantial experience diagnosing chest CT scans for COVID-19, pulmonary embolism, and other forms of lung infections. We present requirements and task analysis for the diagnosis of COVID-19 that motivate our design choices and results in a practical system which is capable of handling real-world patient cases.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Significant work has been done towards deep learning (DL) models for automatic lung and lesion segmentation and classification of COVID-19 on chest CT data. However, comprehensive visualization systems focused on supporting the dual visual+DL diagnosis of COVID-19 are non-existent. We present COVID-view, a visualization application specially tailored for radiologists to diagnose COVID-19 from chest CT data. The system incorporates a complete pipeline of automatic lungs segmentation, localization/isolation of lung abnormalities, followed by visualization, visual and DL analysis, and measurement/quantification tools. Our system combines the traditional 2D workflow of radiologists with newer 2D and 3D visualization techniques with DL support for a more comprehensive diagnosis. COVID-view incorporates a novel DL model for classifying the patients into positive/negative COVID-19 cases, which acts as a reading aid for the radiologist using COVID-view and provides the attention heatmap as an explainable DL for the model output. We designed and evaluated COVID-view through suggestions, close feedback and conducting case studies of real-world patient data by expert radiologists who have substantial experience diagnosing chest CT scans for COVID-19, pulmonary embolism, and other forms of lung infections. We present requirements and task analysis for the diagnosis of COVID-19 that motivate our design choices and results in a practical system which is capable of handling real-world patient cases.",
"title": "<italic>COVID</italic>-view: Diagnosis of COVID-19 using Chest CT",
"normalizedTitle": "COVID-view: Diagnosis of COVID-19 using Chest CT",
"fno": "09552241",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Computerised Tomography",
"Data Visualisation",
"Diagnostic Radiography",
"Image Classification",
"Image Segmentation",
"Lung",
"Medical Image Processing",
"Patient Diagnosis",
"COVID View",
"Automatic Lung",
"Lesion Segmentation",
"Classification",
"Chest CT Data",
"Comprehensive Visualization Systems",
"Radiologist",
"Automatic Lungs Segmentation",
"Substantial Experience Diagnosing Chest CT",
"COVID 19",
"Lung",
"Computed Tomography",
"Visualization",
"Three Dimensional Displays",
"Solid Modeling",
"Lesions",
"Visual Deep Learning Diagnosis",
"COVID 19",
"Chest CT",
"Volume Rendering",
"MIP",
"Classification Model",
"Explainable DL"
],
"authors": [
{
"givenName": "Shreeraj",
"surname": "Jadhav",
"fullName": "Shreeraj Jadhav",
"affiliation": "Department of Computer Science, Stony Brook University, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Gaofeng",
"surname": "Deng",
"fullName": "Gaofeng Deng",
"affiliation": "Department of Computer Science, Stony Brook University, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Marlene",
"surname": "Zawin",
"fullName": "Marlene Zawin",
"affiliation": "Department of Radiology, Stony Brook University Hospital, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Arie E.",
"surname": "Kaufman",
"fullName": "Arie E. Kaufman",
"affiliation": "Department of Computer Science, Stony Brook University, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": false,
"showRecommendedArticles": true,
"isOpenAccess": true,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "227-237",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/big-data/2021/3902/0/09671656",
"title": "Classification of COVID-19 using Deep Learning and Radiomic Texture Features extracted from CT scans of Patients Lungs",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2021/09671656/1A8hnGyzxa8",
"parentPublication": {
"id": "proceedings/big-data/2021/3902/0",
"title": "2021 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/ai/5555/01/09965606",
"title": "Deep Dual Attention Network for Precise Diagnosis of COVID-19 From Chest CT Images",
"doi": null,
"abstractUrl": "/journal/ai/5555/01/09965606/1IHMSiEzkt2",
"parentPublication": {
"id": "trans/ai",
"title": "IEEE Transactions on Artificial Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibe/2022/8487/0/848700a158",
"title": "Attention-based Automated Chest CT Image Segmentation Method of COVID-19 Lung Infection",
"doi": null,
"abstractUrl": "/proceedings-article/bibe/2022/848700a158/1J6hFthOYLe",
"parentPublication": {
"id": "proceedings/bibe/2022/8487/0",
"title": "2022 IEEE 22nd International Conference on Bioinformatics and Bioengineering (BIBE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2022/6819/0/09995590",
"title": "CVD19-Net: An Automated Deep Learning Model for COVID-19 Screening using Chest CT Images",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2022/09995590/1JC1Y85du4E",
"parentPublication": {
"id": "proceedings/bibm/2022/6819/0",
"title": "2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/bd/2021/01/09248607",
"title": "COVID-19-CT-CXR: A Freely Accessible and Weakly Labeled Chest X-Ray and CT Image Collection on COVID-19 From Biomedical Literature",
"doi": null,
"abstractUrl": "/journal/bd/2021/01/09248607/1otZZzqPLMY",
"parentPublication": {
"id": "trans/bd",
"title": "IEEE Transactions on Big Data",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/bd/2021/01/09345435",
"title": "COVID-19 Chest CT Image Segmentation Network by Multi-Scale Fusion and Enhancement Operations",
"doi": null,
"abstractUrl": "/journal/bd/2021/01/09345435/1qTYEs9wmYg",
"parentPublication": {
"id": "trans/bd",
"title": "IEEE Transactions on Big Data",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2021/06/09376253",
"title": "Deep Learning Enables Accurate Diagnosis of Novel Coronavirus (COVID-19) With CT Images",
"doi": null,
"abstractUrl": "/journal/tb/2021/06/09376253/1rSMNzJFMIM",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/ai/2021/03/09378789",
"title": "CovSegNet: A Multi Encoder–Decoder Architecture for Improved Lesion Segmentation of COVID-19 Chest CT Scans",
"doi": null,
"abstractUrl": "/journal/ai/2021/03/09378789/1rZmvrW1Lu8",
"parentPublication": {
"id": "trans/ai",
"title": "IEEE Transactions on Artificial Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2022/05/09508150",
"title": "Automated Diagnosis of COVID-19 Using Deep Supervised Autoencoder With Multi-View Features From CT Images",
"doi": null,
"abstractUrl": "/journal/tb/2022/05/09508150/1vOUcgJh4DS",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/ai/2022/02/09565356",
"title": "Automated COVID-19 Grading With Convolutional Neural Networks in Computed Tomography Scans: A Systematic Comparison",
"doi": null,
"abstractUrl": "/journal/ai/2022/02/09565356/1xx8eiJfTr2",
"parentPublication": {
"id": "trans/ai",
"title": "IEEE Transactions on Artificial Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09617561",
"articleId": "1yA76vDzhhC",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552435",
"articleId": "1xic7UZLov6",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBaVutqXaE",
"name": "ttg202201-09552241s1-supp1-3114851.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552241s1-supp1-3114851.mp4",
"extension": "mp4",
"size": "48.4 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xic7UZLov6",
"doi": "10.1109/TVCG.2021.3114840",
"abstract": "A growing number of longitudinal cohort studies are generating data with extensive patient observations across multiple timepoints. Such data offers promising opportunities to better understand the progression of diseases. However, these observations are usually treated as general events in existing visual analysis tools. As a result, their capabilities in modeling disease progression are not fully utilized. To fill this gap, we designed and implemented ThreadStates, an interactive visual analytics tool for the exploration of longitudinal patient cohort data. The focus of ThreadStates is to identify the states of disease progression by learning from observation data in a human-in-the-loop manner. We propose a novel Glyph Matrix design and combine it with a scatter plot to enable seamless identification, observation, and refinement of states. The disease progression patterns are then revealed in terms of state transitions using Sankey-based visualizations. We employ sequence clustering techniques to find patient groups with distinctive progression patterns, and to reveal the association between disease progression and patient-level features. The design and development were driven by a requirement analysis and iteratively refined based on feedback from domain experts over the course of a 10-month design study. Case studies and expert interviews demonstrate that ThreadStates can successively summarize disease states, reveal disease progression, and compare patient groups.",
"abstracts": [
{
"abstractType": "Regular",
"content": "A growing number of longitudinal cohort studies are generating data with extensive patient observations across multiple timepoints. Such data offers promising opportunities to better understand the progression of diseases. However, these observations are usually treated as general events in existing visual analysis tools. As a result, their capabilities in modeling disease progression are not fully utilized. To fill this gap, we designed and implemented ThreadStates, an interactive visual analytics tool for the exploration of longitudinal patient cohort data. The focus of ThreadStates is to identify the states of disease progression by learning from observation data in a human-in-the-loop manner. We propose a novel Glyph Matrix design and combine it with a scatter plot to enable seamless identification, observation, and refinement of states. The disease progression patterns are then revealed in terms of state transitions using Sankey-based visualizations. We employ sequence clustering techniques to find patient groups with distinctive progression patterns, and to reveal the association between disease progression and patient-level features. The design and development were driven by a requirement analysis and iteratively refined based on feedback from domain experts over the course of a 10-month design study. Case studies and expert interviews demonstrate that ThreadStates can successively summarize disease states, reveal disease progression, and compare patient groups.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "A growing number of longitudinal cohort studies are generating data with extensive patient observations across multiple timepoints. Such data offers promising opportunities to better understand the progression of diseases. However, these observations are usually treated as general events in existing visual analysis tools. As a result, their capabilities in modeling disease progression are not fully utilized. To fill this gap, we designed and implemented ThreadStates, an interactive visual analytics tool for the exploration of longitudinal patient cohort data. The focus of ThreadStates is to identify the states of disease progression by learning from observation data in a human-in-the-loop manner. We propose a novel Glyph Matrix design and combine it with a scatter plot to enable seamless identification, observation, and refinement of states. The disease progression patterns are then revealed in terms of state transitions using Sankey-based visualizations. We employ sequence clustering techniques to find patient groups with distinctive progression patterns, and to reveal the association between disease progression and patient-level features. The design and development were driven by a requirement analysis and iteratively refined based on feedback from domain experts over the course of a 10-month design study. Case studies and expert interviews demonstrate that ThreadStates can successively summarize disease states, reveal disease progression, and compare patient groups.",
"title": "ThreadStates: State-based Visual Analysis of Disease Progression",
"normalizedTitle": "ThreadStates: State-based Visual Analysis of Disease Progression",
"fno": "09552435",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Diseases",
"Data Visualization",
"Hidden Markov Models",
"Visual Analytics",
"Cancer",
"Tools",
"Data Mining",
"Disease Progression",
"State Identification",
"Sequence Visualization"
],
"authors": [
{
"givenName": "Qianwen",
"surname": "Wang",
"fullName": "Qianwen Wang",
"affiliation": "Harvard University, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Tali",
"surname": "Mazor",
"fullName": "Tali Mazor",
"affiliation": "Dana-Farber Cancer Institute, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Theresa A",
"surname": "Harbig",
"fullName": "Theresa A Harbig",
"affiliation": "University of Tübingen, Germany",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Ethan",
"surname": "Cerami",
"fullName": "Ethan Cerami",
"affiliation": "Dana-Farber Cancer Institute, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Nils",
"surname": "Gehlenborg",
"fullName": "Nils Gehlenborg",
"affiliation": "Harvard University, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "238-247",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/cbms/2012/2049/0/06266408",
"title": "Using phase type distributions for modelling HIV disease progression",
"doi": null,
"abstractUrl": "/proceedings-article/cbms/2012/06266408/12OmNAZx8RS",
"parentPublication": {
"id": "proceedings/cbms/2012/2049/0",
"title": "2012 25th IEEE International Symposium on Computer-Based Medical Systems (CBMS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdm/2015/9504/0/9504a721",
"title": "Constructing Disease Network and Temporal Progression Model via Context-Sensitive Hawkes Process",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2015/9504a721/12OmNx7XH5Q",
"parentPublication": {
"id": "proceedings/icdm/2015/9504/0",
"title": "2015 IEEE International Conference on Data Mining (ICDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdmw/2018/9288/0/928800a748",
"title": "Predicting Non-invasive Ventilation in ALS Patients Using Stratified Disease Progression Groups",
"doi": null,
"abstractUrl": "/proceedings-article/icdmw/2018/928800a748/18jXFTMCTD2",
"parentPublication": {
"id": "proceedings/icdmw/2018/9288/0",
"title": "2018 IEEE International Conference on Data Mining Workshops (ICDMW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdm/2021/2398/0/239800a956",
"title": "Temporal Clustering with External Memory Network for Disease Progression Modeling",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2021/239800a956/1Aqxkz7yBkk",
"parentPublication": {
"id": "proceedings/icdm/2021/2398/0",
"title": "2021 IEEE International Conference on Data Mining (ICDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2019/2838/0/283800a405",
"title": "progViz: Visualizing Patient Journeys Based on Finite State Models",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2019/283800a405/1cMFaiuWv2U",
"parentPublication": {
"id": "proceedings/iv/2019/2838/0",
"title": "2019 23rd International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ichi/2019/9138/0/08904698",
"title": "Time-aware Adversarial Networks for Adapting Disease Progression Modeling",
"doi": null,
"abstractUrl": "/proceedings-article/ichi/2019/08904698/1f8NcdJjmve",
"parentPublication": {
"id": "proceedings/ichi/2019/9138/0",
"title": "2019 IEEE International Conference on Healthcare Informatics (ICHI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/09/09058722",
"title": "DPVis: Visual Analytics With Hidden Markov Models for Disease Progression Pathways",
"doi": null,
"abstractUrl": "/journal/tg/2021/09/09058722/1iPJ0xyXzjO",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2020/6215/0/09313376",
"title": "A Predictive Model for Parkinson’s Disease Reveals Candidate Gene Sets for Progression Subtype",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2020/09313376/1qmfTxgaBDG",
"parentPublication": {
"id": "proceedings/bibm/2020/6215/0",
"title": "2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/big-data/2020/6251/0/09377829",
"title": "MuLan: Multilevel Language-based Representation Learning for Disease Progression Modeling",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2020/09377829/1s64GRgtGGQ",
"parentPublication": {
"id": "proceedings/big-data/2020/6251/0",
"title": "2020 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2022/05/09426397",
"title": "Learning Prognostic Models Using Disease Progression Patterns: Predicting the Need for Non-Invasive Ventilation in Amyotrophic Lateral Sclerosis",
"doi": null,
"abstractUrl": "/journal/tb/2022/05/09426397/1tpwPnLMVnW",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552241",
"articleId": "1xic6RdmNC8",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552235",
"articleId": "1xibYn0KqGY",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xibYn0KqGY",
"doi": "10.1109/TVCG.2021.3114766",
"abstract": "Which drug is most promising for a cancer patient? A new microscopy-based approach for measuring the mass of individual cancer cells treated with different drugs promises to answer this question in only a few hours. However, the analysis pipeline for extracting data from these images is still far from complete automation: human intervention is necessary for quality control for preprocessing steps such as segmentation, adjusting filters, removing noise, and analyzing the result. To address this workflow, we developed Loon, a visualization tool for analyzing drug screening data based on quantitative phase microscopy imaging. Loon visualizes both derived data such as growth rates and imaging data. Since the images are collected automatically at a large scale, manual inspection of images and segmentations is infeasible. However, reviewing representative samples of cells is essential, both for quality control and for data analysis. We introduce a new approach for choosing and visualizing representative exemplar cells that retain a close connection to the low-level data. By tightly integrating the derived data visualization capabilities with the novel exemplar visualization and providing selection and filtering capabilities, Loon is well suited for making decisions about which drugs are suitable for a specific patient.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Which drug is most promising for a cancer patient? A new microscopy-based approach for measuring the mass of individual cancer cells treated with different drugs promises to answer this question in only a few hours. However, the analysis pipeline for extracting data from these images is still far from complete automation: human intervention is necessary for quality control for preprocessing steps such as segmentation, adjusting filters, removing noise, and analyzing the result. To address this workflow, we developed Loon, a visualization tool for analyzing drug screening data based on quantitative phase microscopy imaging. Loon visualizes both derived data such as growth rates and imaging data. Since the images are collected automatically at a large scale, manual inspection of images and segmentations is infeasible. However, reviewing representative samples of cells is essential, both for quality control and for data analysis. We introduce a new approach for choosing and visualizing representative exemplar cells that retain a close connection to the low-level data. By tightly integrating the derived data visualization capabilities with the novel exemplar visualization and providing selection and filtering capabilities, Loon is well suited for making decisions about which drugs are suitable for a specific patient.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Which drug is most promising for a cancer patient? A new microscopy-based approach for measuring the mass of individual cancer cells treated with different drugs promises to answer this question in only a few hours. However, the analysis pipeline for extracting data from these images is still far from complete automation: human intervention is necessary for quality control for preprocessing steps such as segmentation, adjusting filters, removing noise, and analyzing the result. To address this workflow, we developed Loon, a visualization tool for analyzing drug screening data based on quantitative phase microscopy imaging. Loon visualizes both derived data such as growth rates and imaging data. Since the images are collected automatically at a large scale, manual inspection of images and segmentations is infeasible. However, reviewing representative samples of cells is essential, both for quality control and for data analysis. We introduce a new approach for choosing and visualizing representative exemplar cells that retain a close connection to the low-level data. By tightly integrating the derived data visualization capabilities with the novel exemplar visualization and providing selection and filtering capabilities, Loon is well suited for making decisions about which drugs are suitable for a specific patient.",
"title": "Loon: Using Exemplars to Visualize Large-Scale Microscopy Data",
"normalizedTitle": "Loon: Using Exemplars to Visualize Large-Scale Microscopy Data",
"fno": "09552235",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Biomedical Optical Imaging",
"Cancer",
"Cellular Biophysics",
"Data Analysis",
"Data Visualisation",
"Drugs",
"Image Segmentation",
"Medical Image Processing",
"Optical Microscopy",
"Quality Control",
"Loon",
"Exemplars",
"Large Scale Microscopy Data",
"Drug",
"Cancer Patient",
"Microscopy Based Approach",
"Individual Cancer Cells",
"Different Drugs Promises",
"Analysis Pipeline",
"Complete Automation",
"Human Intervention",
"Quality Control",
"Visualization Tool",
"Quantitative Phase Microscopy Imaging",
"Growth Rates",
"Imaging Data",
"Data Analysis",
"Representative Exemplar Cells",
"Low Level Data",
"Derived Data Visualization Capabilities",
"Novel Exemplar Visualization",
"Providing Selection",
"Specific Patient",
"Data Visualization",
"Image Segmentation",
"Microscopy",
"Imaging",
"Cancer",
"Tools",
"Tumors",
"Microscopy Visualization",
"Cancer Cell Lines",
"Exemplars",
"Design Study"
],
"authors": [
{
"givenName": "Devin",
"surname": "Lange",
"fullName": "Devin Lange",
"affiliation": "University of Utah, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Eddie",
"surname": "Polanco",
"fullName": "Eddie Polanco",
"affiliation": "University of Utah, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Robert",
"surname": "Judson-Torres",
"fullName": "Robert Judson-Torres",
"affiliation": "University of Utah, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Thomas",
"surname": "Zangle",
"fullName": "Thomas Zangle",
"affiliation": "University of Utah, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Alexander",
"surname": "Lex",
"fullName": "Alexander Lex",
"affiliation": "University of Utah, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "248-258",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/bibm/2017/3050/0/08217827",
"title": "Mitochondria segmentation in electron microscopy volumes using deep convolutional neural network",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2017/08217827/12OmNBTawxv",
"parentPublication": {
"id": "proceedings/bibm/2017/3050/0",
"title": "2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvprw/2017/0733/0/0733a851",
"title": "Transferring Microscopy Image Modalities with Conditional Generative Adversarial Networks",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2017/0733a851/12OmNwGIcza",
"parentPublication": {
"id": "proceedings/cvprw/2017/0733/0",
"title": "2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvprw/2017/0733/0/0733a834",
"title": "Nuclei Segmentation of Fluorescence Microscopy Images Using Three Dimensional Convolutional Neural Networks",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2017/0733a834/12OmNwlHSTo",
"parentPublication": {
"id": "proceedings/cvprw/2017/0733/0",
"title": "2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmtma/2011/4296/2/4296c943",
"title": "Raman Microscopy and Imaging in Pharmaceutical Applications",
"doi": null,
"abstractUrl": "/proceedings-article/icmtma/2011/4296c943/12OmNxiKs4x",
"parentPublication": {
"id": "proceedings/icmtma/2011/4296/2",
"title": "2011 Third International Conference on Measuring Technology and Mechatronics Automation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2011/1799/0/06120462",
"title": "Computer-Based Image Analysis of Liver Steatosis with Large-Scale Microscopy Imagery and Correlation with Magnetic Resonance Imaging Lipid Analysis",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2011/06120462/12OmNz4BduY",
"parentPublication": {
"id": "proceedings/bibm/2011/1799/0",
"title": "2011 IEEE International Conference on Bioinformatics and Biomedicine",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2015/03/06963495",
"title": "Extraction of Individual Filaments from 2D Confocal Microscopy Images of Flat Cells",
"doi": null,
"abstractUrl": "/journal/tb/2015/03/06963495/13rRUwIF6jt",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvprw/2018/6100/0/610000c371",
"title": "Localization and Tracking in 4D Fluorescence Microscopy Imagery",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2018/610000c371/17D45VsBTWj",
"parentPublication": {
"id": "proceedings/cvprw/2018/6100/0",
"title": "2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2018/3788/0/08546040",
"title": "Multi-label Classification of Stem Cell Microscopy Images Using Deep Learning",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2018/08546040/17D45WZZ7GJ",
"parentPublication": {
"id": "proceedings/icpr/2018/3788/0",
"title": "2018 24th International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/01/08440805",
"title": "Visualization of Neuronal Structures in Wide-Field Microscopy Brain Images",
"doi": null,
"abstractUrl": "/journal/tg/2019/01/08440805/17D45WnnFUX",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2021/8808/0/09412641",
"title": "Learning to segment clustered amoeboid cells from brightfield microscopy via multi-task learning with adaptive weight selection",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2021/09412641/1tmiarePQAg",
"parentPublication": {
"id": "proceedings/icpr/2021/8808/0",
"title": "2020 25th International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552435",
"articleId": "1xic7UZLov6",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09557792",
"articleId": "1xquHxMLASQ",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBavFuFKRW",
"name": "ttg202201-09552235s1-supp1-3114766.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552235s1-supp1-3114766.mp4",
"extension": "mp4",
"size": "122 MB",
"__typename": "WebExtraType"
},
{
"id": "1zBavyKQdoY",
"name": "ttg202201-09552235s1-supp2-3114766.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552235s1-supp2-3114766.pdf",
"extension": "pdf",
"size": "2.88 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xquHxMLASQ",
"doi": "10.1109/TVCG.2021.3114786",
"abstract": "Inspection of tissues using a light microscope is the primary method of diagnosing many diseases, notably cancer. Highly multiplexed tissue imaging builds on this foundation, enabling the collection of up to 60 channels of molecular information plus cell and tissue morphology using antibody staining. This provides unique insight into disease biology and promises to help with the design of patient-specific therapies. However, a substantial gap remains with respect to visualizing the resulting multivariate image data and effectively supporting pathology workflows in digital environments on screen. We, therefore, developed Scope2Screen, a scalable software system for focus+context exploration and annotation of whole-slide, high-plex, tissue images. Our approach scales to analyzing 100GB images of 10<sup>9</sup> or more pixels per channel, containing millions of individual cells. A multidisciplinary team of visualization experts, microscopists, and pathologists identified key image exploration and annotation tasks involving finding, magnifying, quantifying, and organizing regions of interest (ROIs) in an intuitive and cohesive manner. Building on a scope-to-screen metaphor, we present interactive lensing techniques that operate at single-cell and tissue levels. Lenses are equipped with task-specific functionality and descriptive statistics, making it possible to analyze image features, cell types, and spatial arrangements (neighborhoods) across image channels and scales. A fast sliding-window search guides users to regions similar to those under the lens; these regions can be analyzed and considered either separately or as part of a larger image collection. A novel snapshot method enables linked lens configurations and image statistics to be saved, restored, and shared with these regions. We validate our designs with domain experts and apply Scope2Screen in two case studies involving lung and colorectal cancers to discover cancer-relevant image features.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Inspection of tissues using a light microscope is the primary method of diagnosing many diseases, notably cancer. Highly multiplexed tissue imaging builds on this foundation, enabling the collection of up to 60 channels of molecular information plus cell and tissue morphology using antibody staining. This provides unique insight into disease biology and promises to help with the design of patient-specific therapies. However, a substantial gap remains with respect to visualizing the resulting multivariate image data and effectively supporting pathology workflows in digital environments on screen. We, therefore, developed Scope2Screen, a scalable software system for focus+context exploration and annotation of whole-slide, high-plex, tissue images. Our approach scales to analyzing 100GB images of 10<sup>9</sup> or more pixels per channel, containing millions of individual cells. A multidisciplinary team of visualization experts, microscopists, and pathologists identified key image exploration and annotation tasks involving finding, magnifying, quantifying, and organizing regions of interest (ROIs) in an intuitive and cohesive manner. Building on a scope-to-screen metaphor, we present interactive lensing techniques that operate at single-cell and tissue levels. Lenses are equipped with task-specific functionality and descriptive statistics, making it possible to analyze image features, cell types, and spatial arrangements (neighborhoods) across image channels and scales. A fast sliding-window search guides users to regions similar to those under the lens; these regions can be analyzed and considered either separately or as part of a larger image collection. A novel snapshot method enables linked lens configurations and image statistics to be saved, restored, and shared with these regions. We validate our designs with domain experts and apply Scope2Screen in two case studies involving lung and colorectal cancers to discover cancer-relevant image features.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Inspection of tissues using a light microscope is the primary method of diagnosing many diseases, notably cancer. Highly multiplexed tissue imaging builds on this foundation, enabling the collection of up to 60 channels of molecular information plus cell and tissue morphology using antibody staining. This provides unique insight into disease biology and promises to help with the design of patient-specific therapies. However, a substantial gap remains with respect to visualizing the resulting multivariate image data and effectively supporting pathology workflows in digital environments on screen. We, therefore, developed Scope2Screen, a scalable software system for focus+context exploration and annotation of whole-slide, high-plex, tissue images. Our approach scales to analyzing 100GB images of 109 or more pixels per channel, containing millions of individual cells. A multidisciplinary team of visualization experts, microscopists, and pathologists identified key image exploration and annotation tasks involving finding, magnifying, quantifying, and organizing regions of interest (ROIs) in an intuitive and cohesive manner. Building on a scope-to-screen metaphor, we present interactive lensing techniques that operate at single-cell and tissue levels. Lenses are equipped with task-specific functionality and descriptive statistics, making it possible to analyze image features, cell types, and spatial arrangements (neighborhoods) across image channels and scales. A fast sliding-window search guides users to regions similar to those under the lens; these regions can be analyzed and considered either separately or as part of a larger image collection. A novel snapshot method enables linked lens configurations and image statistics to be saved, restored, and shared with these regions. We validate our designs with domain experts and apply Scope2Screen in two case studies involving lung and colorectal cancers to discover cancer-relevant image features.",
"title": "Scope2Screen: Focus+Context Techniques for Pathology Tumor Assessment in Multivariate Image Data",
"normalizedTitle": "Scope2Screen: Focus+Context Techniques for Pathology Tumor Assessment in Multivariate Image Data",
"fno": "09557792",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Lenses",
"Tools",
"Task Analysis",
"Data Visualization",
"Annotations",
"Cancer",
"Rendering Computer Graphics",
"Histopathology",
"Focus Context",
"Image Analysis"
],
"authors": [
{
"givenName": "Jared",
"surname": "Jessup",
"fullName": "Jared Jessup",
"affiliation": "School of Engineering and Applied Sciences, Harvard University, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Robert",
"surname": "Krueger",
"fullName": "Robert Krueger",
"affiliation": "School of Engineering and Applied Sciences, Harvard University, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Simon",
"surname": "Warchol",
"fullName": "Simon Warchol",
"affiliation": "School of Engineering and Applied Sciences, Harvard University, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "John",
"surname": "Hoffer",
"fullName": "John Hoffer",
"affiliation": "Laboratory of Systems Pharmacology, Harvard Medical School, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jeremy",
"surname": "Muhlich",
"fullName": "Jeremy Muhlich",
"affiliation": "Laboratory of Systems Pharmacology, Harvard Medical School, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Cecily C.",
"surname": "Ritch",
"fullName": "Cecily C. Ritch",
"affiliation": "Brigham and Women's Hospital, Harvard Medical School, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Giorgio",
"surname": "Gaglia",
"fullName": "Giorgio Gaglia",
"affiliation": "Brigham and Women's Hospital, Harvard Medical School, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Shannon",
"surname": "Coy",
"fullName": "Shannon Coy",
"affiliation": "Brigham and Women's Hospital, Harvard Medical School, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yu-An",
"surname": "Chen",
"fullName": "Yu-An Chen",
"affiliation": "Laboratory of Systems Pharmacology, Harvard Medical School, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jia-Ren",
"surname": "Lin",
"fullName": "Jia-Ren Lin",
"affiliation": "Laboratory of Systems Pharmacology, Harvard Medical School, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Sandro",
"surname": "Santagata",
"fullName": "Sandro Santagata",
"affiliation": "Brigham and Women's Hospital, Harvard Medical School, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Peter K.",
"surname": "Sorger",
"fullName": "Peter K. Sorger",
"affiliation": "Laboratory of Systems Pharmacology, Harvard Medical School, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Hanspeter",
"surname": "Pfister",
"fullName": "Hanspeter Pfister",
"affiliation": "School of Engineering and Applied Sciences, Harvard University, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "259-269",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/icpr/2008/2174/0/04760936",
"title": "2. Image computing for digital pathology",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2008/04760936/12OmNqzcvDi",
"parentPublication": {
"id": "proceedings/icpr/2008/2174/0",
"title": "ICPR 2008 19th International Conference on Pattern Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2017/3050/0/08217719",
"title": "Deep learning assessment of tumor proliferation in breast cancer histological images",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2017/08217719/12OmNrNh0v7",
"parentPublication": {
"id": "proceedings/bibm/2017/3050/0",
"title": "2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2014/5209/0/5209c053",
"title": "Masking Light Fields to Remove Partial Occlusion",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2014/5209c053/12OmNvmowMP",
"parentPublication": {
"id": "proceedings/icpr/2014/5209/0",
"title": "2014 22nd International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccvw/2009/4442/0/05457520",
"title": "Single image focus editing",
"doi": null,
"abstractUrl": "/proceedings-article/iccvw/2009/05457520/12OmNxwWozJ",
"parentPublication": {
"id": "proceedings/iccvw/2009/4442/0",
"title": "2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ieee-vis/2005/2766/0/01532818",
"title": "The magic volume lens: an interactive focus+context technique for volume rendering",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-vis/2005/01532818/12OmNyuyade",
"parentPublication": {
"id": "proceedings/ieee-vis/2005/2766/0",
"title": "Visualization Conference, IEEE",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2017/07/07460953",
"title": "User-Perspective AR Magic Lens from Gradient-Based IBR and Semi-Dense Stereo",
"doi": null,
"abstractUrl": "/journal/tg/2017/07/07460953/13rRUILc8ff",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/08/08396300",
"title": "Decal-Lenses: Interactive Lenses on Surfaces for Multivariate Visualization",
"doi": null,
"abstractUrl": "/journal/tg/2019/08/08396300/13rRUyeCkap",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2020/01/08827951",
"title": "Facetto: Combining Unsupervised and Supervised Learning for Hierarchical Phenotype Analysis in Multi-Channel Image Data",
"doi": null,
"abstractUrl": "/journal/tg/2020/01/08827951/1ddbk50fzNK",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2020/7168/0/716800f163",
"title": "Single Image Reflection Removal With Physically-Based Training Images",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2020/716800f163/1m3neuoHr8Y",
"parentPublication": {
"id": "proceedings/cvpr/2020/7168/0",
"title": "2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccvw/2021/0191/0/019100a674",
"title": "Robust Interactive Semantic Segmentation of Pathology Images with Minimal User Input",
"doi": null,
"abstractUrl": "/proceedings-article/iccvw/2021/019100a674/1yNhVjPgGWY",
"parentPublication": {
"id": "proceedings/iccvw/2021/0191/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552235",
"articleId": "1xibYn0KqGY",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552857",
"articleId": "1xibYEW20Vy",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBaDKN8gc8",
"name": "ttg202201-09557792s1-supp2-3114786.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09557792s1-supp2-3114786.pdf",
"extension": "pdf",
"size": "99.7 kB",
"__typename": "WebExtraType"
},
{
"id": "1zBaDRyWZzy",
"name": "ttg202201-09557792s1-supp1-3114786.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09557792s1-supp1-3114786.mp4",
"extension": "mp4",
"size": "161 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xibYEW20Vy",
"doi": "10.1109/TVCG.2021.3114815",
"abstract": "We present STNet, an end-to-end generative framework that synthesizes spatiotemporal super-resolution volumes with high fidelity for time-varying data. STNet includes two modules: a generator and a spatiotemporal discriminator. The input to the generator is two low-resolution volumes at both ends, and the output is the intermediate and the two-ending spatiotemporal super-resolution volumes. The spatiotemporal discriminator, leveraging convolutional long short-term memory, accepts a spatiotemporal super-resolution sequence as input and predicts a conditional score for each volume based on its spatial (the volume itself) and temporal (the previous volumes) information. We propose an unsupervised pre-training stage using cycle loss to improve the generalization of STNet. Once trained, STNet can generate spatiotemporal super-resolution volumes from low-resolution ones, offering scientists an option to save data storage (i.e., sparsely sampling the simulation output in both spatial and temporal dimensions). We compare STNet with the baseline bicubic+linear interpolation, two deep learning solutions (<inline-formula><tex-math notation=\"LaTeX\">Z_$\\mathsf{SSR}+\\mathsf{TSF}$_Z</tex-math></inline-formula>, STD), and a state-of-the-art tensor compression solution (TTHRESH) to show the effectiveness of STNet.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We present STNet, an end-to-end generative framework that synthesizes spatiotemporal super-resolution volumes with high fidelity for time-varying data. STNet includes two modules: a generator and a spatiotemporal discriminator. The input to the generator is two low-resolution volumes at both ends, and the output is the intermediate and the two-ending spatiotemporal super-resolution volumes. The spatiotemporal discriminator, leveraging convolutional long short-term memory, accepts a spatiotemporal super-resolution sequence as input and predicts a conditional score for each volume based on its spatial (the volume itself) and temporal (the previous volumes) information. We propose an unsupervised pre-training stage using cycle loss to improve the generalization of STNet. Once trained, STNet can generate spatiotemporal super-resolution volumes from low-resolution ones, offering scientists an option to save data storage (i.e., sparsely sampling the simulation output in both spatial and temporal dimensions). We compare STNet with the baseline bicubic+linear interpolation, two deep learning solutions (<inline-formula><tex-math notation=\"LaTeX\">$\\mathsf{SSR}+\\mathsf{TSF}$</tex-math><alternatives><graphic position=\"float\" orientation=\"portrait\" xlink:href=\"28tvcg01-han-3114815-eqinline-1-small.tif\"/></alternatives></inline-formula>, STD), and a state-of-the-art tensor compression solution (TTHRESH) to show the effectiveness of STNet.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We present STNet, an end-to-end generative framework that synthesizes spatiotemporal super-resolution volumes with high fidelity for time-varying data. STNet includes two modules: a generator and a spatiotemporal discriminator. The input to the generator is two low-resolution volumes at both ends, and the output is the intermediate and the two-ending spatiotemporal super-resolution volumes. The spatiotemporal discriminator, leveraging convolutional long short-term memory, accepts a spatiotemporal super-resolution sequence as input and predicts a conditional score for each volume based on its spatial (the volume itself) and temporal (the previous volumes) information. We propose an unsupervised pre-training stage using cycle loss to improve the generalization of STNet. Once trained, STNet can generate spatiotemporal super-resolution volumes from low-resolution ones, offering scientists an option to save data storage (i.e., sparsely sampling the simulation output in both spatial and temporal dimensions). We compare STNet with the baseline bicubic+linear interpolation, two deep learning solutions (-, STD), and a state-of-the-art tensor compression solution (TTHRESH) to show the effectiveness of STNet.",
"title": "STNet: An End-to-End Generative Framework for Synthesizing Spatiotemporal Super-Resolution Volumes",
"normalizedTitle": "STNet: An End-to-End Generative Framework for Synthesizing Spatiotemporal Super-Resolution Volumes",
"fno": "09552857",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Image Reconstruction",
"Image Resolution",
"Interpolation",
"Learning Artificial Intelligence",
"Medical Image Processing",
"Tensors",
"ST Net",
"End To End Generative Framework",
"Spatiotemporal Super Resolution Volumes",
"Spatiotemporal Discriminator",
"Low Resolution Volumes",
"Spatiotemporal Super Resolution Sequence",
"Spatiotemporal Phenomena",
"Superresolution",
"Interpolation",
"Training",
"Task Analysis",
"Deep Learning",
"Feature Extraction",
"Time Varying Data",
"Generative Adversarial Network",
"Spatiotemporal Super Resolution"
],
"authors": [
{
"givenName": "Jun",
"surname": "Han",
"fullName": "Jun Han",
"affiliation": "Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Hao",
"surname": "Zheng",
"fullName": "Hao Zheng",
"affiliation": "Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Danny Z.",
"surname": "Chen",
"fullName": "Danny Z. Chen",
"affiliation": "Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Chaoli",
"surname": "Wang",
"fullName": "Chaoli Wang",
"affiliation": "Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "270-280",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/comgeo/2014/4321/0/06910112",
"title": "A Spatiotemporal Interpolation Method Using Radial Basis Functions for Geospatiotemporal Big Data",
"doi": null,
"abstractUrl": "/proceedings-article/comgeo/2014/06910112/12OmNzYeAQE",
"parentPublication": {
"id": "proceedings/comgeo/2014/4321/0",
"title": "2014 5th International Conference on Computing for Geospatial Research and Application (COM.Geo)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2021/2812/0/281200e460",
"title": "Event Stream Super-Resolution via Spatiotemporal Constraint Learning",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/281200e460/1BmHTcxfM7S",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cisai/2021/0692/0/069200a704",
"title": "Video Super Resolution Based on Motion Compensation",
"doi": null,
"abstractUrl": "/proceedings-article/cisai/2021/069200a704/1BmOrPEdpO8",
"parentPublication": {
"id": "proceedings/cisai/2021/0692/0",
"title": "2021 International Conference on Computer Information Science and Artificial Intelligence (CISAI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2022/6946/0/694600f962",
"title": "BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and Alignment",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600f962/1H1kq191zva",
"parentPublication": {
"id": "proceedings/cvpr/2022/6946/0",
"title": "2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/avss/2022/6382/0/09959711",
"title": "Dual Camera Based High Spatio-Temporal Resolution Video Generation For Wide Area Surveillance",
"doi": null,
"abstractUrl": "/proceedings-article/avss/2022/09959711/1Iz59B0m2as",
"parentPublication": {
"id": "proceedings/avss/2022/6382/0",
"title": "2022 18th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/07/08941308",
"title": "Local Prediction Models for Spatiotemporal Volume Visualization",
"doi": null,
"abstractUrl": "/journal/tg/2021/07/08941308/1g1FWXBrTxe",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacv/2020/6553/0/09093564",
"title": "Cloud Removal in Satellite Images Using Spatiotemporal Generative Networks",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2020/09093564/1jPbnrgXMly",
"parentPublication": {
"id": "proceedings/wacv/2020/6553/0",
"title": "2020 IEEE Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2020/7168/0/716800e725",
"title": "A Spatiotemporal Volumetric Interpolation Network for 4D Dynamic Medical Image",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2020/716800e725/1m3o6jEDHEY",
"parentPublication": {
"id": "proceedings/cvpr/2020/7168/0",
"title": "2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2021/3864/0/09428231",
"title": "STAE: A Spatiotemporal Auto-Encoder for High-Resolution Video Prediction",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2021/09428231/1uilMLOlmaA",
"parentPublication": {
"id": "proceedings/icme/2021/3864/0",
"title": "2021 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacv/2021/0477/0/047700c683",
"title": "Dual-Stream Fusion Network for Spatiotemporal Video Super-Resolution",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2021/047700c683/1uqGlWkmblK",
"parentPublication": {
"id": "proceedings/wacv/2021/0477/0",
"title": "2021 IEEE Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09557792",
"articleId": "1xquHxMLASQ",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09556604",
"articleId": "1xlvXSp8cco",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBaxatrfwc",
"name": "ttg202201-09552857s1-supp1-3114815.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552857s1-supp1-3114815.pdf",
"extension": "pdf",
"size": "4.77 MB",
"__typename": "WebExtraType"
},
{
"id": "1zBawUHQJy0",
"name": "ttg202201-09552857s1-supp2-3114815.wmv",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552857s1-supp2-3114815.wmv",
"extension": "wmv",
"size": "40.2 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xlvXSp8cco",
"doi": "10.1109/TVCG.2021.3115565",
"abstract": "State-of-the-art computation and visualization of vortices in unsteady fluid flow employ objective vortex criteria, which makes them independent of reference frames or observers. However, objectivity by itself, although crucial, is not sufficient to guarantee that one can identify physically-realizable observers that would perceive or detect the same vortices. Moreover, a significant challenge is that a single reference frame is often not sufficient to accurately observe multiple vortices that follow different motions. This paper presents a novel framework for the exploration and use of an interactively-chosen set of observers, of the resulting relative velocity fields, and of objective vortex structures. We show that our approach facilitates the objective detection and visualization of vortices relative to well-adapted reference frame motions, while at the same time guaranteeing that these observers are in fact physically realizable. In order to represent and manipulate observers efficiently, we make use of the low-dimensional vector space structure of the Lie algebra of physically-realizable observer motions. We illustrate that our framework facilitates the efficient choice and guided exploration of objective vortices in unsteady 2D flow, on planar as well as on spherical domains, using well-adapted reference frames.",
"abstracts": [
{
"abstractType": "Regular",
"content": "State-of-the-art computation and visualization of vortices in unsteady fluid flow employ objective vortex criteria, which makes them independent of reference frames or observers. However, objectivity by itself, although crucial, is not sufficient to guarantee that one can identify physically-realizable observers that would perceive or detect the same vortices. Moreover, a significant challenge is that a single reference frame is often not sufficient to accurately observe multiple vortices that follow different motions. This paper presents a novel framework for the exploration and use of an interactively-chosen set of observers, of the resulting relative velocity fields, and of objective vortex structures. We show that our approach facilitates the objective detection and visualization of vortices relative to well-adapted reference frame motions, while at the same time guaranteeing that these observers are in fact physically realizable. In order to represent and manipulate observers efficiently, we make use of the low-dimensional vector space structure of the Lie algebra of physically-realizable observer motions. We illustrate that our framework facilitates the efficient choice and guided exploration of objective vortices in unsteady 2D flow, on planar as well as on spherical domains, using well-adapted reference frames.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "State-of-the-art computation and visualization of vortices in unsteady fluid flow employ objective vortex criteria, which makes them independent of reference frames or observers. However, objectivity by itself, although crucial, is not sufficient to guarantee that one can identify physically-realizable observers that would perceive or detect the same vortices. Moreover, a significant challenge is that a single reference frame is often not sufficient to accurately observe multiple vortices that follow different motions. This paper presents a novel framework for the exploration and use of an interactively-chosen set of observers, of the resulting relative velocity fields, and of objective vortex structures. We show that our approach facilitates the objective detection and visualization of vortices relative to well-adapted reference frame motions, while at the same time guaranteeing that these observers are in fact physically realizable. In order to represent and manipulate observers efficiently, we make use of the low-dimensional vector space structure of the Lie algebra of physically-realizable observer motions. We illustrate that our framework facilitates the efficient choice and guided exploration of objective vortices in unsteady 2D flow, on planar as well as on spherical domains, using well-adapted reference frames.",
"title": "Interactive Exploration of Physically-Observable Objective Vortices in Unsteady 2D Flow",
"normalizedTitle": "Interactive Exploration of Physically-Observable Objective Vortices in Unsteady 2D Flow",
"fno": "09556604",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"External Flows",
"Flow Simulation",
"Lie Algebras",
"Motion Estimation",
"Object Detection",
"Vectors",
"Vortices",
"Interactive Exploration",
"Physically Observable Objective Vortices",
"Unsteady 2 D Flow",
"Visualization",
"Unsteady Fluid Flow",
"Objective Vortex Criteria",
"Objectivity",
"Physically Realizable Observers",
"Single Reference Frame",
"Multiple Vortices",
"Resulting Relative Velocity Fields",
"Objective Vortex Structures",
"Objective Detection",
"Reference Frame Motions",
"Physically Realizable Observer Motions",
"Well Adapted Reference Frames",
"Observers",
"Visualization",
"Algebra",
"Interpolation",
"Optimization",
"Manifolds",
"Feature Extraction",
"Flow Visualization",
"Vortex Detection",
"Objectivity",
"Observers",
"Reference Frames",
"Lie Algebras"
],
"authors": [
{
"givenName": "Xingdi",
"surname": "Zhang",
"fullName": "Xingdi Zhang",
"affiliation": "King Abdullah University of Science and Technology (KAUST), Visual Computing Center, Thuwal, Saudi Arabia",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Markus",
"surname": "Hadwiger",
"fullName": "Markus Hadwiger",
"affiliation": "King Abdullah University of Science and Technology (KAUST), Visual Computing Center, Thuwal, Saudi Arabia",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Thomas",
"surname": "Theußl",
"fullName": "Thomas Theußl",
"affiliation": "King Abdullah University of Science and Technology (KAUST), Core Labs, Thuwal, Saudi Arabia",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Peter",
"surname": "Rautek",
"fullName": "Peter Rautek",
"affiliation": "King Abdullah University of Science and Technology (KAUST), Visual Computing Center, Thuwal, Saudi Arabia",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "281-290",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/visual/1994/6627/0/00346328",
"title": "3D visualization of unsteady 2D airplane wake vortices",
"doi": null,
"abstractUrl": "/proceedings-article/visual/1994/00346328/12OmNroij7B",
"parentPublication": {
"id": "proceedings/visual/1994/6627/0",
"title": "Proceedings Visualization '94",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/01/08440037",
"title": "Time-Dependent Flow seen through Approximate Observer Killing Fields",
"doi": null,
"abstractUrl": "/journal/tg/2019/01/08440037/17D45X2fUEW",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/02/09222512",
"title": "Objective Observer-Relative Flow Visualization in Curved Spaces for Unsteady 2D Geophysical Flows",
"doi": null,
"abstractUrl": "/journal/tg/2021/02/09222512/1nTq2foekVO",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552857",
"articleId": "1xibYEW20Vy",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09555911",
"articleId": "1xlvYjicn7i",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBap0yztWU",
"name": "ttg202201-09556604s1-supp1-3115565.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09556604s1-supp1-3115565.mp4",
"extension": "mp4",
"size": "74.3 MB",
"__typename": "WebExtraType"
},
{
"id": "1zBaoVhzA6A",
"name": "ttg202201-09556604s1-supp2-3115565.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09556604s1-supp2-3115565.pdf",
"extension": "pdf",
"size": "803 kB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xlvYjicn7i",
"doi": "10.1109/TVCG.2021.3114839",
"abstract": "This paper presents a unified computational framework for the estimation of distances, geodesics and barycenters of merge trees. We extend recent work on the edit distance [104] and introduce a new metric, called the Wasserstein distance between merge trees, which is purposely designed to enable efficient computations of geodesics and barycenters. Specifically, our new distance is strictly equivalent to the Z_$L$_Z2-Wasserstein distance between extremum persistence diagrams, but it is restricted to a smaller solution space, namely, the space of rooted partial isomorphisms between branch decomposition trees. This enables a simple extension of existing optimization frameworks [110] for geodesics and barycenters from persistence diagrams to merge trees. We introduce a task-based algorithm which can be generically applied to distance, geodesic, barycenter or cluster computation. The task-based nature of our approach enables further accelerations with shared-memory parallelism. Extensive experiments on public ensembles and SciVis contest benchmarks demonstrate the efficiency of our approach - with barycenter computations in the orders of minutes for the largest examples - as well as its qualitative ability to generate representative barycenter merge trees, visually summarizing the features of interest found in the ensemble. We show the utility of our contributions with dedicated visualization applications: feature tracking, temporal reduction and ensemble clustering. We provide a lightweight C++ implementation that can be used to reproduce our results.",
"abstracts": [
{
"abstractType": "Regular",
"content": "This paper presents a unified computational framework for the estimation of distances, geodesics and barycenters of merge trees. We extend recent work on the edit distance [104] and introduce a new metric, called the Wasserstein distance between merge trees, which is purposely designed to enable efficient computations of geodesics and barycenters. Specifically, our new distance is strictly equivalent to the $L$2-Wasserstein distance between extremum persistence diagrams, but it is restricted to a smaller solution space, namely, the space of rooted partial isomorphisms between branch decomposition trees. This enables a simple extension of existing optimization frameworks [110] for geodesics and barycenters from persistence diagrams to merge trees. We introduce a task-based algorithm which can be generically applied to distance, geodesic, barycenter or cluster computation. The task-based nature of our approach enables further accelerations with shared-memory parallelism. Extensive experiments on public ensembles and SciVis contest benchmarks demonstrate the efficiency of our approach - with barycenter computations in the orders of minutes for the largest examples - as well as its qualitative ability to generate representative barycenter merge trees, visually summarizing the features of interest found in the ensemble. We show the utility of our contributions with dedicated visualization applications: feature tracking, temporal reduction and ensemble clustering. We provide a lightweight C++ implementation that can be used to reproduce our results.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "This paper presents a unified computational framework for the estimation of distances, geodesics and barycenters of merge trees. We extend recent work on the edit distance [104] and introduce a new metric, called the Wasserstein distance between merge trees, which is purposely designed to enable efficient computations of geodesics and barycenters. Specifically, our new distance is strictly equivalent to the -2-Wasserstein distance between extremum persistence diagrams, but it is restricted to a smaller solution space, namely, the space of rooted partial isomorphisms between branch decomposition trees. This enables a simple extension of existing optimization frameworks [110] for geodesics and barycenters from persistence diagrams to merge trees. We introduce a task-based algorithm which can be generically applied to distance, geodesic, barycenter or cluster computation. The task-based nature of our approach enables further accelerations with shared-memory parallelism. Extensive experiments on public ensembles and SciVis contest benchmarks demonstrate the efficiency of our approach - with barycenter computations in the orders of minutes for the largest examples - as well as its qualitative ability to generate representative barycenter merge trees, visually summarizing the features of interest found in the ensemble. We show the utility of our contributions with dedicated visualization applications: feature tracking, temporal reduction and ensemble clustering. We provide a lightweight C++ implementation that can be used to reproduce our results.",
"title": "Wasserstein Distances, Geodesics and Barycenters of Merge Trees",
"normalizedTitle": "Wasserstein Distances, Geodesics and Barycenters of Merge Trees",
"fno": "09555911",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Data Visualization",
"Measurement",
"Task Analysis",
"Probability Density Function",
"Uncertainty",
"Market Research",
"Data Models",
"Topological Data Analysis",
"Merge Trees",
"Scalar Data",
"Ensemble Data"
],
"authors": [
{
"givenName": "Mathieu",
"surname": "Pont",
"fullName": "Mathieu Pont",
"affiliation": "Sorbonne Université and CNRS, France",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jules",
"surname": "Vidal",
"fullName": "Jules Vidal",
"affiliation": "Sorbonne Université and CNRS, France",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Julie",
"surname": "Delon",
"fullName": "Julie Delon",
"affiliation": "University of Paris, France",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Julien",
"surname": "Tierny",
"fullName": "Julien Tierny",
"affiliation": "Sorbonne Université and CNRS, France",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "291-301",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/ldav/2017/0617/0/08231846",
"title": "Task-based augmented merge trees with Fibonacci heaps",
"doi": null,
"abstractUrl": "/proceedings-article/ldav/2017/08231846/12OmNzBwGrc",
"parentPublication": {
"id": "proceedings/ldav/2017/0617/0",
"title": "2017 IEEE 7th Symposium on Large Data Analysis and Visualization (LDAV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2020/03/08481543",
"title": "Edit Distance between Merge Trees",
"doi": null,
"abstractUrl": "/journal/tg/2020/03/08481543/146z4GS1UPK",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09744472",
"title": "Geometry Aware Merge Tree Comparisons for Time-Varying Data with Interleaving Distances",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09744472/1C8BFCieD2U",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09912347",
"title": "Computing a Stable Distance on Merge Trees",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09912347/1HeiTQ2soFO",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/02/09920234",
"title": "Principal Geodesic Analysis of Merge Trees (and Persistence Diagrams)",
"doi": null,
"abstractUrl": "/journal/tg/2023/02/09920234/1HxSnktOqgU",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/topoinvis/2022/9354/0/935400a029",
"title": "A Deformation-based Edit Distance for Merge Trees",
"doi": null,
"abstractUrl": "/proceedings-article/topoinvis/2022/935400a029/1J2XJrPDCgM",
"parentPublication": {
"id": "proceedings/topoinvis/2022/9354/0",
"title": "2022 Topological Data Analysis and Visualization (TopoInVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2020/01/08794517",
"title": "Progressive Wasserstein Barycenters of Persistence Diagrams",
"doi": null,
"abstractUrl": "/journal/tg/2020/01/08794517/1cr2YZjGkPm",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2020/01/08794553",
"title": "A Structural Average of Labeled Merge Trees for Uncertainty Visualization",
"doi": null,
"abstractUrl": "/journal/tg/2020/01/08794553/1fe7uYD8R68",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/08/09420248",
"title": "Unordered Task-Parallel Augmented Merge Tree Construction",
"doi": null,
"abstractUrl": "/journal/tg/2021/08/09420248/1tdUMuQErm0",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2021/4509/0/450900q6780",
"title": "Wasserstein Barycenter for Multi-Source Domain Adaptation",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2021/450900q6780/1yeKpVhavUk",
"parentPublication": {
"id": "proceedings/cvpr/2021/4509/0",
"title": "2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09556604",
"articleId": "1xlvXSp8cco",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552880",
"articleId": "1xic21fTTva",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBaupxe9Zm",
"name": "ttg202201-09555911s1-tvcg-3114839-mm.zip",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09555911s1-tvcg-3114839-mm.zip",
"extension": "zip",
"size": "183 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xic21fTTva",
"doi": "10.1109/TVCG.2021.3114872",
"abstract": "Persistence diagrams have been widely used to quantify the underlying features of filtered topological spaces in data visualization. In many applications, computing distances between diagrams is essential; however, computing these distances has been challenging due to the computational cost. In this paper, we propose a persistence diagram hashing framework that learns a binary code representation of persistence diagrams, which allows for fast computation of distances. This framework is built upon a generative adversarial network (GAN) with a diagram distance loss function to steer the learning process. Instead of using standard representations, we hash diagrams into binary codes, which have natural advantages in large-scale tasks. The training of this model is domain-oblivious in that it can be computed purely from synthetic, randomly created diagrams. As a consequence, our proposed method is directly applicable to various datasets without the need for retraining the model. These binary codes, when compared using fast Hamming distance, better maintain topological similarity properties between datasets than other vectorized representations. To evaluate this method, we apply our framework to the problem of diagram clustering and we compare the quality and performance of our approach to the state-of-the-art. In addition, we show the scalability of our approach on a dataset with 10k persistence diagrams, which is not possible with current techniques. Moreover, our experimental results demonstrate that our method is significantly faster with the potential of less memory usage, while retaining comparable or better quality comparisons.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Persistence diagrams have been widely used to quantify the underlying features of filtered topological spaces in data visualization. In many applications, computing distances between diagrams is essential; however, computing these distances has been challenging due to the computational cost. In this paper, we propose a persistence diagram hashing framework that learns a binary code representation of persistence diagrams, which allows for fast computation of distances. This framework is built upon a generative adversarial network (GAN) with a diagram distance loss function to steer the learning process. Instead of using standard representations, we hash diagrams into binary codes, which have natural advantages in large-scale tasks. The training of this model is domain-oblivious in that it can be computed purely from synthetic, randomly created diagrams. As a consequence, our proposed method is directly applicable to various datasets without the need for retraining the model. These binary codes, when compared using fast Hamming distance, better maintain topological similarity properties between datasets than other vectorized representations. To evaluate this method, we apply our framework to the problem of diagram clustering and we compare the quality and performance of our approach to the state-of-the-art. In addition, we show the scalability of our approach on a dataset with 10k persistence diagrams, which is not possible with current techniques. Moreover, our experimental results demonstrate that our method is significantly faster with the potential of less memory usage, while retaining comparable or better quality comparisons.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Persistence diagrams have been widely used to quantify the underlying features of filtered topological spaces in data visualization. In many applications, computing distances between diagrams is essential; however, computing these distances has been challenging due to the computational cost. In this paper, we propose a persistence diagram hashing framework that learns a binary code representation of persistence diagrams, which allows for fast computation of distances. This framework is built upon a generative adversarial network (GAN) with a diagram distance loss function to steer the learning process. Instead of using standard representations, we hash diagrams into binary codes, which have natural advantages in large-scale tasks. The training of this model is domain-oblivious in that it can be computed purely from synthetic, randomly created diagrams. As a consequence, our proposed method is directly applicable to various datasets without the need for retraining the model. These binary codes, when compared using fast Hamming distance, better maintain topological similarity properties between datasets than other vectorized representations. To evaluate this method, we apply our framework to the problem of diagram clustering and we compare the quality and performance of our approach to the state-of-the-art. In addition, we show the scalability of our approach on a dataset with 10k persistence diagrams, which is not possible with current techniques. Moreover, our experimental results demonstrate that our method is significantly faster with the potential of less memory usage, while retaining comparable or better quality comparisons.",
"title": "A Domain-Oblivious Approach for Learning Concise Representations of Filtered Topological Spaces for Clustering",
"normalizedTitle": "A Domain-Oblivious Approach for Learning Concise Representations of Filtered Topological Spaces for Clustering",
"fno": "09552880",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Binary Codes",
"Training",
"Propagation Losses",
"Histograms",
"Generative Adversarial Networks",
"Hash Functions",
"Water Resources",
"Topological Data Analysis",
"Persistence Diagrams",
"Persistence Diagram Distances",
"Learned Hashing",
"Clustering"
],
"authors": [
{
"givenName": "Yu",
"surname": "Qin",
"fullName": "Yu Qin",
"affiliation": "Tulane University, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Brittany Terese",
"surname": "Fasy",
"fullName": "Brittany Terese Fasy",
"affiliation": "Montana State University, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Carola",
"surname": "Wenk",
"fullName": "Carola Wenk",
"affiliation": "Tulane University, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Brian",
"surname": "Summa",
"fullName": "Brian Summa",
"affiliation": "Tulane University, United States",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "302-312",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/ldav/2022/9156/0/09966403",
"title": "Topological Analysis of Ensembles of Hydrodynamic Turbulent Flows An Experimental Study",
"doi": null,
"abstractUrl": "/proceedings-article/ldav/2022/09966403/1IT0Ck3lBg4",
"parentPublication": {
"id": "proceedings/ldav/2022/9156/0",
"title": "2022 IEEE 12th Symposium on Large Data Analysis and Visualization (LDAV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/big-data/2022/8045/0/10020423",
"title": "Stable Topological Feature Vectors via Hermite Function Expansion on Persistence Curves",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2022/10020423/1KfRC2DMiJy",
"parentPublication": {
"id": "proceedings/big-data/2022/8045/0",
"title": "2022 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icnc/2023/5719/0/10074146",
"title": "Evaluating Generative Adversarial Networks: A Topological Approach",
"doi": null,
"abstractUrl": "/proceedings-article/icnc/2023/10074146/1LKwEhgRbQ4",
"parentPublication": {
"id": "proceedings/icnc/2023/5719/0",
"title": "2023 International Conference on Computing, Networking and Communications (ICNC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09555911",
"articleId": "1xlvYjicn7i",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552919",
"articleId": "1xibXgJW32U",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xibXgJW32U",
"doi": "10.1109/TVCG.2021.3114795",
"abstract": "Edge bundling techniques cluster edges with similar attributes (i.e. similarity in direction and proximity) together to reduce the visual clutter. All edge bundling techniques to date implicitly or explicitly cluster groups of individual edges, or parts of them, together based on these attributes. These clusters can result in ambiguous connections that do not exist in the data. Confluent drawings of networks do not have these ambiguities, but require the layout to be computed as part of the bundling process. We devise a new bundling method, Edge-Path bundling, to simplify edge clutter while greatly reducing ambiguities compared to previous bundling techniques. Edge-Path bundling takes a layout as input and clusters each edge along a weighted, shortest path to limit its deviation from a straight line. Edge-Path bundling does not incur independent edge ambiguities typically seen in all edge bundling methods, and the level of bundling can be tuned through shortest path distances, Euclidean distances, and combinations of the two. Also, directed edge bundling naturally emerges from the model. Through metric evaluations, we demonstrate the advantages of Edge-Path bundling over other techniques.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Edge bundling techniques cluster edges with similar attributes (i.e. similarity in direction and proximity) together to reduce the visual clutter. All edge bundling techniques to date implicitly or explicitly cluster groups of individual edges, or parts of them, together based on these attributes. These clusters can result in ambiguous connections that do not exist in the data. Confluent drawings of networks do not have these ambiguities, but require the layout to be computed as part of the bundling process. We devise a new bundling method, Edge-Path bundling, to simplify edge clutter while greatly reducing ambiguities compared to previous bundling techniques. Edge-Path bundling takes a layout as input and clusters each edge along a weighted, shortest path to limit its deviation from a straight line. Edge-Path bundling does not incur independent edge ambiguities typically seen in all edge bundling methods, and the level of bundling can be tuned through shortest path distances, Euclidean distances, and combinations of the two. Also, directed edge bundling naturally emerges from the model. Through metric evaluations, we demonstrate the advantages of Edge-Path bundling over other techniques.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Edge bundling techniques cluster edges with similar attributes (i.e. similarity in direction and proximity) together to reduce the visual clutter. All edge bundling techniques to date implicitly or explicitly cluster groups of individual edges, or parts of them, together based on these attributes. These clusters can result in ambiguous connections that do not exist in the data. Confluent drawings of networks do not have these ambiguities, but require the layout to be computed as part of the bundling process. We devise a new bundling method, Edge-Path bundling, to simplify edge clutter while greatly reducing ambiguities compared to previous bundling techniques. Edge-Path bundling takes a layout as input and clusters each edge along a weighted, shortest path to limit its deviation from a straight line. Edge-Path bundling does not incur independent edge ambiguities typically seen in all edge bundling methods, and the level of bundling can be tuned through shortest path distances, Euclidean distances, and combinations of the two. Also, directed edge bundling naturally emerges from the model. Through metric evaluations, we demonstrate the advantages of Edge-Path bundling over other techniques.",
"title": "Edge-Path Bundling: A Less Ambiguous Edge Bundling Approach",
"normalizedTitle": "Edge-Path Bundling: A Less Ambiguous Edge Bundling Approach",
"fno": "09552919",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Computational Geometry",
"Data Visualisation",
"Edge Detection",
"Graph Theory",
"Pattern Clustering",
"Edge Path Bundling",
"Independent Edge Ambiguities",
"Edge Bundling Methods",
"Directed Edge Bundling",
"Ambiguous Edge Bundling Approach",
"Edge Bundling Techniques",
"Edge Clutter",
"Previous Bundling Techniques",
"Layout",
"Image Edge Detection",
"Clutter",
"Windings",
"Roads",
"Visualization",
"Lakes",
"Graph Network And Tree Data",
"Algorithms",
"Edge Bundling"
],
"authors": [
{
"givenName": "Markus",
"surname": "Wallinger",
"fullName": "Markus Wallinger",
"affiliation": "TU Wien, Austria",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Daniel",
"surname": "Archambault",
"fullName": "Daniel Archambault",
"affiliation": "Swansea University, United Kingdom",
"__typename": "ArticleAuthorType"
},
{
"givenName": "David",
"surname": "Auber",
"fullName": "David Auber",
"affiliation": "University of Bordeaux, France",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Martin",
"surname": "Nöllenburg",
"fullName": "Martin Nöllenburg",
"affiliation": "TU Wien, Austria",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jaakko",
"surname": "Peltonen",
"fullName": "Jaakko Peltonen",
"affiliation": "Tampere University, Finland",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "313-323",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/pacificvis/2015/6879/0/07156354",
"title": "Attribute-driven edge bundling for general graphs with applications in trail analysis",
"doi": null,
"abstractUrl": "/proceedings-article/pacificvis/2015/07156354/12OmNCaLEnG",
"parentPublication": {
"id": "proceedings/pacificvis/2015/6879/0",
"title": "2015 IEEE Pacific Visualization Symposium (PacificVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pacificvis/2016/1451/0/07465267",
"title": "Multilayer graph edge bundling",
"doi": null,
"abstractUrl": "/proceedings-article/pacificvis/2016/07465267/12OmNCbCrKh",
"parentPublication": {
"id": "proceedings/pacificvis/2016/1451/0",
"title": "2016 IEEE Pacific Visualization Symposium (PacificVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2010/7846/0/05571244",
"title": "3D Edge Bundling for Geographical Data Visualization",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2010/05571244/12OmNqzu6LL",
"parentPublication": {
"id": "proceedings/iv/2010/7846/0",
"title": "2010 14th International Conference Information Visualisation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pacificvis/2014/2874/0/2874a057",
"title": "An Edge-Bundling Layout for Interactive Parallel Coordinates",
"doi": null,
"abstractUrl": "/proceedings-article/pacificvis/2014/2874a057/12OmNwEJ0Cx",
"parentPublication": {
"id": "proceedings/pacificvis/2014/2874/0",
"title": "2014 IEEE Pacific Visualization Symposium (PacificVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pacificvis/2011/935/0/05742389",
"title": "Multilevel agglomerative edge bundling for visualizing large graphs",
"doi": null,
"abstractUrl": "/proceedings-article/pacificvis/2011/05742389/12OmNxj233Y",
"parentPublication": {
"id": "proceedings/pacificvis/2011/935/0",
"title": "2011 IEEE Pacific Visualization Symposium (PacificVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/dsc/2016/1192/0/1192a466",
"title": "Research on Network Simplification by Edge Bundling",
"doi": null,
"abstractUrl": "/proceedings-article/dsc/2016/1192a466/12OmNyQpgKZ",
"parentPublication": {
"id": "proceedings/dsc/2016/1192/0",
"title": "2016 IEEE First International Conference on Data Science in Cyberspace (DSC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2013/5049/0/5049a028",
"title": "Edge Bundling by Rapidly-Exploring Random Trees",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2013/5049a028/12OmNz5s0F9",
"parentPublication": {
"id": "proceedings/iv/2013/5049/0",
"title": "2013 17th International Conference on Information Visualisation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pacificvis/2017/5738/0/08031594",
"title": "FFTEB: Edge bundling of huge graphs by the Fast Fourier Transform",
"doi": null,
"abstractUrl": "/proceedings-article/pacificvis/2017/08031594/12OmNzuZUEs",
"parentPublication": {
"id": "proceedings/pacificvis/2017/5738/0",
"title": "2017 IEEE Pacific Visualization Symposium (PacificVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2017/01/07539373",
"title": "Towards Unambiguous Edge Bundling: Investigating Confluent Drawings for Network Visualization",
"doi": null,
"abstractUrl": "/journal/tg/2017/01/07539373/13rRUwcS1CZ",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2011/12/ttg2011122354",
"title": "Divided Edge Bundling for Directional Network Data",
"doi": null,
"abstractUrl": "/journal/tg/2011/12/ttg2011122354/13rRUzpzeB1",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552880",
"articleId": "1xic21fTTva",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09556579",
"articleId": "1xlw0LJ4OTm",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBaquRkllC",
"name": "ttg202201-09552919s1-tvcg-3114795-mm.zip",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552919s1-tvcg-3114795-mm.zip",
"extension": "zip",
"size": "367 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xlw0LJ4OTm",
"doi": "10.1109/TVCG.2021.3114756",
"abstract": "Node-link visualizations are a familiar and powerful tool for displaying the relationships in a network. The readability of these visualizations highly depends on the spatial layout used for the nodes. In this paper, we focus on computing <italic>layered</italic> layouts, in which nodes are aligned on a set of parallel axes to better expose hierarchical or sequential relationships. Heuristic-based layouts are widely used as they scale well to larger networks and usually create readable, albeit sub-optimal, visualizations. We instead use a <italic>layout optimization model</italic> that prioritizes <italic>optimality</italic> - as compared to <italic>scalability</italic> - because an optimal solution not only represents the best attainable result, but can also serve as a baseline to evaluate the effectiveness of layout heuristics. We take an important step towards powerful and flexible network visualization by proposing S<sc>tratisfimal</sc> L<sc>ayout</sc>, a <italic>modular integer-linear-programming formulation</italic> that can consider several important readability criteria <italic>simultaneously</italic> — crossing reduction, edge bendiness, and nested and multi-layer groups. The layout can be adapted to diverse use cases through its modularity. Individual features can be enabled and customized depending on the application. We provide open-source and documented implementations of the layout, both for web-based and desktop visualizations. As a proof-of-concept, we apply it to the problem of visualizing complicated SQL queries, which have features that we believe cannot be addressed by existing layout optimization models. We also include a benchmark network generator and the results of an empirical evaluation to assess the performance trade-offs of our design choices. A full version of this paper with all appendices, data, and source code is available at osf.io/qdyt9 with live examples at <uri>https://visdunneright.github.io/stratisfimal/</uri>.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Node-link visualizations are a familiar and powerful tool for displaying the relationships in a network. The readability of these visualizations highly depends on the spatial layout used for the nodes. In this paper, we focus on computing <italic>layered</italic> layouts, in which nodes are aligned on a set of parallel axes to better expose hierarchical or sequential relationships. Heuristic-based layouts are widely used as they scale well to larger networks and usually create readable, albeit sub-optimal, visualizations. We instead use a <italic>layout optimization model</italic> that prioritizes <italic>optimality</italic> - as compared to <italic>scalability</italic> - because an optimal solution not only represents the best attainable result, but can also serve as a baseline to evaluate the effectiveness of layout heuristics. We take an important step towards powerful and flexible network visualization by proposing S<sc>tratisfimal</sc> L<sc>ayout</sc>, a <italic>modular integer-linear-programming formulation</italic> that can consider several important readability criteria <italic>simultaneously</italic> — crossing reduction, edge bendiness, and nested and multi-layer groups. The layout can be adapted to diverse use cases through its modularity. Individual features can be enabled and customized depending on the application. We provide open-source and documented implementations of the layout, both for web-based and desktop visualizations. As a proof-of-concept, we apply it to the problem of visualizing complicated SQL queries, which have features that we believe cannot be addressed by existing layout optimization models. We also include a benchmark network generator and the results of an empirical evaluation to assess the performance trade-offs of our design choices. A full version of this paper with all appendices, data, and source code is available at osf.io/qdyt9 with live examples at <uri>https://visdunneright.github.io/stratisfimal/</uri>.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Node-link visualizations are a familiar and powerful tool for displaying the relationships in a network. The readability of these visualizations highly depends on the spatial layout used for the nodes. In this paper, we focus on computing layered layouts, in which nodes are aligned on a set of parallel axes to better expose hierarchical or sequential relationships. Heuristic-based layouts are widely used as they scale well to larger networks and usually create readable, albeit sub-optimal, visualizations. We instead use a layout optimization model that prioritizes optimality - as compared to scalability - because an optimal solution not only represents the best attainable result, but can also serve as a baseline to evaluate the effectiveness of layout heuristics. We take an important step towards powerful and flexible network visualization by proposing Stratisfimal Layout, a modular integer-linear-programming formulation that can consider several important readability criteria simultaneously — crossing reduction, edge bendiness, and nested and multi-layer groups. The layout can be adapted to diverse use cases through its modularity. Individual features can be enabled and customized depending on the application. We provide open-source and documented implementations of the layout, both for web-based and desktop visualizations. As a proof-of-concept, we apply it to the problem of visualizing complicated SQL queries, which have features that we believe cannot be addressed by existing layout optimization models. We also include a benchmark network generator and the results of an empirical evaluation to assess the performance trade-offs of our design choices. A full version of this paper with all appendices, data, and source code is available at osf.io/qdyt9 with live examples at https://visdunneright.github.io/stratisfimal/.",
"title": "STRATISFIMAL LAYOUT: A modular optimization model for laying out layered node-link network visualizations",
"normalizedTitle": "STRATISFIMAL LAYOUT: A modular optimization model for laying out layered node-link network visualizations",
"fno": "09556579",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Layout",
"Structured Query Language",
"Visualization",
"Optimization",
"Scalability",
"Integer Linear Programming",
"Computational Modeling",
"Layered Node Link Visualization",
"Integer Linear Programming",
"Crossing Reduction",
"Bendiness Reduction",
"Nested Groups"
],
"authors": [
{
"givenName": "Sara",
"surname": "di Bartolomeo",
"fullName": "Sara di Bartolomeo",
"affiliation": "Northeastern University, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Mirek",
"surname": "Riedewald",
"fullName": "Mirek Riedewald",
"affiliation": "Northeastern University, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Wolfgang",
"surname": "Gatterbauer",
"fullName": "Wolfgang Gatterbauer",
"affiliation": "Northeastern University, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Cody",
"surname": "Dunne",
"fullName": "Cody Dunne",
"affiliation": "Northeastern University, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "324-334",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/iv/2011/0868/0/06004064",
"title": "Listening to Managers: A Study about Visualizations in Corporate Presentations",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2011/06004064/12OmNqBbHF8",
"parentPublication": {
"id": "proceedings/iv/2011/0868/0",
"title": "2011 15th International Conference on Information Visualisation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pacificvis/2013/4797/0/06596147",
"title": "On the faithfulness of graph visualizations",
"doi": null,
"abstractUrl": "/proceedings-article/pacificvis/2013/06596147/12OmNwCJON7",
"parentPublication": {
"id": "proceedings/pacificvis/2013/4797/0",
"title": "2013 IEEE Pacific Visualization Symposium (PacificVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ieee-infovis/1997/8189/0/81890002",
"title": "H3: laying out large directed graphs in 3D hyperbolic space",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-infovis/1997/81890002/12OmNwEJ10t",
"parentPublication": {
"id": "proceedings/ieee-infovis/1997/8189/0",
"title": "Information Visualization, IEEE Symposium on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2017/0831/0/0831a288",
"title": "Sketch-Based Interactions for Untangling of Force-Directed Graphs",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2017/0831a288/12OmNyO8tVY",
"parentPublication": {
"id": "proceedings/iv/2017/0831/0",
"title": "2017 21st International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2018/12/08233127",
"title": "Atom: A Grammar for Unit Visualizations",
"doi": null,
"abstractUrl": "/journal/tg/2018/12/08233127/14H4WLzSYsE",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09904490",
"title": "A Scanner Deeply: Predicting Gaze Heatmaps on Visualizations Using Crowdsourced Eye Movement Data",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09904490/1H1gj9xTTG0",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09916137",
"title": "Revisiting the Design Patterns of Composite Visualizations",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09916137/1HojAjSAGNq",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09917516",
"title": "Geo-Storylines: Integrating Maps into Storyline Visualizations",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09917516/1HrexIf2zZe",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09984953",
"title": "VISAtlas: An Image-based Exploration and Query System for Large Visualization Collections via Neural Image Embedding",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09984953/1J6d2SwfUT6",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/02/09165928",
"title": "Hybrid Graph Visualizations With ChordLink: Algorithms, Experiments, and Applications",
"doi": null,
"abstractUrl": "/journal/tg/2022/02/09165928/1mevWoz3hM4",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552919",
"articleId": "1xibXgJW32U",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552902",
"articleId": "1xic4qsF8zK",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBaFXEllsI",
"name": "ttg202201-09556579s1-tvcg-3114756-mm.zip",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09556579s1-tvcg-3114756-mm.zip",
"extension": "zip",
"size": "55.4 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xic4qsF8zK",
"doi": "10.1109/TVCG.2021.3114857",
"abstract": "Graphs are a ubiquitous data structure to model processes and relations in a wide range of domains. Examples include control-flow graphs in programs and semantic scene graphs in images. Identifying subgraph patterns in graphs is an important approach to understand their structural properties. We propose a visual analytics system GraphQ to support human-in-the-loop, example-based, subgraph pattern search in a database containing many individual graphs. To support fast, interactive queries, we use graph neural networks (GNNs) to encode a graph as fixed-length latent vector representation, and perform subgraph matching in the latent space. Due to the complexity of the problem, it is still difficult to obtain accurate one-to-one node correspondences in the matching results that are crucial for visualization and interpretation. We, therefore, propose a novel GNN for node-alignment called NeuroAlign, to facilitate easy validation and interpretation of the query results. GraphQ provides a visual query interface with a query editor and a multi-scale visualization of the results, as well as a user feedback mechanism for refining the results with additional constraints. We demonstrate GraphQ through two example usage scenarios: analyzing reusable subroutines in program workflows and semantic scene graph search in images. Quantitative experiments show that NeuroAlign achieves 19%-29% improvement in node-alignment accuracy compared to baseline GNN and provides up to 100× speedup compared to combinatorial algorithms. Our qualitative study with domain experts confirms the effectiveness for both usage scenarios.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Graphs are a ubiquitous data structure to model processes and relations in a wide range of domains. Examples include control-flow graphs in programs and semantic scene graphs in images. Identifying subgraph patterns in graphs is an important approach to understand their structural properties. We propose a visual analytics system GraphQ to support human-in-the-loop, example-based, subgraph pattern search in a database containing many individual graphs. To support fast, interactive queries, we use graph neural networks (GNNs) to encode a graph as fixed-length latent vector representation, and perform subgraph matching in the latent space. Due to the complexity of the problem, it is still difficult to obtain accurate one-to-one node correspondences in the matching results that are crucial for visualization and interpretation. We, therefore, propose a novel GNN for node-alignment called NeuroAlign, to facilitate easy validation and interpretation of the query results. GraphQ provides a visual query interface with a query editor and a multi-scale visualization of the results, as well as a user feedback mechanism for refining the results with additional constraints. We demonstrate GraphQ through two example usage scenarios: analyzing reusable subroutines in program workflows and semantic scene graph search in images. Quantitative experiments show that NeuroAlign achieves 19%-29% improvement in node-alignment accuracy compared to baseline GNN and provides up to 100× speedup compared to combinatorial algorithms. Our qualitative study with domain experts confirms the effectiveness for both usage scenarios.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Graphs are a ubiquitous data structure to model processes and relations in a wide range of domains. Examples include control-flow graphs in programs and semantic scene graphs in images. Identifying subgraph patterns in graphs is an important approach to understand their structural properties. We propose a visual analytics system GraphQ to support human-in-the-loop, example-based, subgraph pattern search in a database containing many individual graphs. To support fast, interactive queries, we use graph neural networks (GNNs) to encode a graph as fixed-length latent vector representation, and perform subgraph matching in the latent space. Due to the complexity of the problem, it is still difficult to obtain accurate one-to-one node correspondences in the matching results that are crucial for visualization and interpretation. We, therefore, propose a novel GNN for node-alignment called NeuroAlign, to facilitate easy validation and interpretation of the query results. GraphQ provides a visual query interface with a query editor and a multi-scale visualization of the results, as well as a user feedback mechanism for refining the results with additional constraints. We demonstrate GraphQ through two example usage scenarios: analyzing reusable subroutines in program workflows and semantic scene graph search in images. Quantitative experiments show that NeuroAlign achieves 19%-29% improvement in node-alignment accuracy compared to baseline GNN and provides up to 100× speedup compared to combinatorial algorithms. Our qualitative study with domain experts confirms the effectiveness for both usage scenarios.",
"title": "Interactive Visual Pattern Search on Graph Data via Graph Representation Learning",
"normalizedTitle": "Interactive Visual Pattern Search on Graph Data via Graph Representation Learning",
"fno": "09552902",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Task Analysis",
"Semantics",
"Visual Analytics",
"Graph Neural Networks",
"Computational Modeling",
"Visual Databases",
"Pattern Matching",
"Graph",
"Graph Neural Network",
"Representation Learning",
"Visual Query Interface"
],
"authors": [
{
"givenName": "Huan",
"surname": "Song",
"fullName": "Huan Song",
"affiliation": "Robert Bosch Research and Technology Center, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Zeng",
"surname": "Dai",
"fullName": "Zeng Dai",
"affiliation": "ByteDance Inc., China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Panpan",
"surname": "Xu",
"fullName": "Panpan Xu",
"affiliation": "Amazon AWS AI, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Liu",
"surname": "Ren",
"fullName": "Liu Ren",
"affiliation": "Robert Bosch Research and Technology Center, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "335-345",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/cvpr/1996/7258/0/72580239",
"title": "Graph matching by graduated assignment",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/1996/72580239/12OmNANBZq3",
"parentPublication": {
"id": "proceedings/cvpr/1996/7258/0",
"title": "Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/dta/2015/9849/0/9849a001",
"title": "Graph Pattern Matching through Model Checking",
"doi": null,
"abstractUrl": "/proceedings-article/dta/2015/9849a001/12OmNvBIRPs",
"parentPublication": {
"id": "proceedings/dta/2015/9849/0",
"title": "2015 8th International Conference on Database Theory and Application (DTA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2015/7964/0/07113411",
"title": "DaVinci: Data-driven visual interface construction for subgraph search in graph databases",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2015/07113411/12OmNwHQB6n",
"parentPublication": {
"id": "proceedings/icde/2015/7964/0",
"title": "2015 IEEE 31st International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/mue/2009/3658/0/3658a353",
"title": "A Directed Labeled Graph Frequent Pattern Mining Algorithm Based on Minimum Code",
"doi": null,
"abstractUrl": "/proceedings-article/mue/2009/3658a353/12OmNxETaaF",
"parentPublication": {
"id": "proceedings/mue/2009/3658/0",
"title": "Multimedia and Ubiquitous Engineering, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2009/3545/0/3545a393",
"title": "Continuous Subgraph Pattern Search over Graph Streams",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2009/3545a393/12OmNyPQ4yV",
"parentPublication": {
"id": "proceedings/icde/2009/3545/0",
"title": "2009 IEEE 25th International Conference on Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdar/2011/4520/0/4520a870",
"title": "Subgraph Spotting through Explicit Graph Embedding: An Application to Content Spotting in Graphic Document Images",
"doi": null,
"abstractUrl": "/proceedings-article/icdar/2011/4520a870/12OmNzX6cm2",
"parentPublication": {
"id": "proceedings/icdar/2011/4520/0",
"title": "2011 International Conference on Document Analysis and Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2010/08/ttk2010081093",
"title": "Continuous Subgraph Pattern Search over Certain and Uncertain Graph Streams",
"doi": null,
"abstractUrl": "/journal/tk/2010/08/ttk2010081093/13rRUxly9el",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2022/0883/0/088300d150",
"title": "VICS-GNN: A Visual Interactive System for Community Search via Graph Neural Network",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2022/088300d150/1FwBCyhqyXK",
"parentPublication": {
"id": "proceedings/icde/2022/0883/0",
"title": "2022 IEEE 38th International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdm/2022/5099/0/509900b095",
"title": "Improving Graph Representation Learning with Distribution Preserving",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2022/509900b095/1KpCwhzN9m0",
"parentPublication": {
"id": "proceedings/icdm/2022/5099/0",
"title": "2022 IEEE International Conference on Data Mining (ICDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdm/2020/8316/0/831600a432",
"title": "Tree Structure-Aware Graph Representation Learning via Integrated Hierarchical Aggregation and Relational Metric Learning",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2020/831600a432/1r54H2s0tu8",
"parentPublication": {
"id": "proceedings/icdm/2020/8316/0",
"title": "2020 IEEE International Conference on Data Mining (ICDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09556579",
"articleId": "1xlw0LJ4OTm",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552925",
"articleId": "1xibWnPGM5a",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBaOx3HDhe",
"name": "ttg202201-09552902s1-supp1-3114857.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552902s1-supp1-3114857.pdf",
"extension": "pdf",
"size": "399 kB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xibWnPGM5a",
"doi": "10.1109/TVCG.2021.3114814",
"abstract": "Although we have seen a proliferation of algorithms for recommending visualizations, these algorithms are rarely compared with one another, making it difficult to ascertain which algorithm is best for a given visual analysis scenario. Though several formal frameworks have been proposed in response, we believe this issue persists because visualization recommendation algorithms are inadequately specified from an <italic>evaluation</italic> perspective. In this paper, we propose an evaluation-focused framework to contextualize and compare a broad range of visualization recommendation algorithms. We present the structure of our framework, where algorithms are specified using three components: (1) a graph representing the full space of possible visualization designs, (2) the method used to traverse the graph for potential candidates for recommendation, and (3) an oracle used to rank candidate designs. To demonstrate how our framework guides the formal comparison of algorithmic performance, we not only theoretically compare five existing representative recommendation algorithms, but also empirically compare four new algorithms generated based on our findings from the theoretical comparison. Our results show that these algorithms behave similarly in terms of user performance, highlighting the need for more rigorous formal comparisons of recommendation algorithms to further clarify their benefits in various analysis scenarios.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Although we have seen a proliferation of algorithms for recommending visualizations, these algorithms are rarely compared with one another, making it difficult to ascertain which algorithm is best for a given visual analysis scenario. Though several formal frameworks have been proposed in response, we believe this issue persists because visualization recommendation algorithms are inadequately specified from an <italic>evaluation</italic> perspective. In this paper, we propose an evaluation-focused framework to contextualize and compare a broad range of visualization recommendation algorithms. We present the structure of our framework, where algorithms are specified using three components: (1) a graph representing the full space of possible visualization designs, (2) the method used to traverse the graph for potential candidates for recommendation, and (3) an oracle used to rank candidate designs. To demonstrate how our framework guides the formal comparison of algorithmic performance, we not only theoretically compare five existing representative recommendation algorithms, but also empirically compare four new algorithms generated based on our findings from the theoretical comparison. Our results show that these algorithms behave similarly in terms of user performance, highlighting the need for more rigorous formal comparisons of recommendation algorithms to further clarify their benefits in various analysis scenarios.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Although we have seen a proliferation of algorithms for recommending visualizations, these algorithms are rarely compared with one another, making it difficult to ascertain which algorithm is best for a given visual analysis scenario. Though several formal frameworks have been proposed in response, we believe this issue persists because visualization recommendation algorithms are inadequately specified from an evaluation perspective. In this paper, we propose an evaluation-focused framework to contextualize and compare a broad range of visualization recommendation algorithms. We present the structure of our framework, where algorithms are specified using three components: (1) a graph representing the full space of possible visualization designs, (2) the method used to traverse the graph for potential candidates for recommendation, and (3) an oracle used to rank candidate designs. To demonstrate how our framework guides the formal comparison of algorithmic performance, we not only theoretically compare five existing representative recommendation algorithms, but also empirically compare four new algorithms generated based on our findings from the theoretical comparison. Our results show that these algorithms behave similarly in terms of user performance, highlighting the need for more rigorous formal comparisons of recommendation algorithms to further clarify their benefits in various analysis scenarios.",
"title": "An Evaluation-Focused Framework for Visualization Recommendation Algorithms",
"normalizedTitle": "An Evaluation-Focused Framework for Visualization Recommendation Algorithms",
"fno": "09552925",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Data Visualisation",
"Formal Specification",
"Formal Verification",
"Graph Theory",
"Recommender Systems",
"Software Quality",
"Evaluation Focused Framework",
"Visualization Recommendation Algorithms",
"Recommending Visualizations",
"Given Visual Analysis Scenario",
"Formal Frameworks",
"Possible Visualization Designs",
"Algorithmic Performance",
"Existing Representative Recommendation Algorithms",
"Data Visualization",
"Visualization",
"Machine Learning Algorithms",
"Approximation Algorithms",
"Task Analysis",
"Encoding",
"Clustering Algorithms",
"Visualization Tools",
"Visualization Recommendation Algorithms"
],
"authors": [
{
"givenName": "Zehua",
"surname": "Zeng",
"fullName": "Zehua Zeng",
"affiliation": "University of Maryland, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Phoebe",
"surname": "Moh",
"fullName": "Phoebe Moh",
"affiliation": "University of Maryland, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Fan",
"surname": "Du",
"fullName": "Fan Du",
"affiliation": "Adobe Research, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jane",
"surname": "Hoffswell",
"fullName": "Jane Hoffswell",
"affiliation": "Adobe Research, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Tak Yeon",
"surname": "Lee",
"fullName": "Tak Yeon Lee",
"affiliation": "Adobe Research, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Sana",
"surname": "Malik",
"fullName": "Sana Malik",
"affiliation": "Adobe Research, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Eunyee",
"surname": "Koh",
"fullName": "Eunyee Koh",
"affiliation": "Adobe Research, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Leilani",
"surname": "Battle",
"fullName": "Leilani Battle",
"affiliation": "University of Maryland, United States",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "346-356",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/grc/2014/5464/0/06982839",
"title": "On semantic evaluation of text clustering algorithms",
"doi": null,
"abstractUrl": "/proceedings-article/grc/2014/06982839/12OmNvSbBBZ",
"parentPublication": {
"id": "proceedings/grc/2014/5464/0",
"title": "2014 IEEE International Conference on Granular Computing (GrC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/asonam/2015/3854/0/07403630",
"title": "GraphExploiter: Creation, visualization and algorithms on graphs",
"doi": null,
"abstractUrl": "/proceedings-article/asonam/2015/07403630/12OmNzXFoCU",
"parentPublication": {
"id": "proceedings/asonam/2015/3854/0",
"title": "2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2016/03/07312976",
"title": "A Graph-Based Taxonomy of Recommendation Algorithms and Systems in LBSNs",
"doi": null,
"abstractUrl": "/journal/tk/2016/03/07312976/13rRUIM2VHt",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icbk/2018/9125/0/912500a139",
"title": "Snapshot Visualization of Complex Graphs with Force-Directed Algorithms",
"doi": null,
"abstractUrl": "/proceedings-article/icbk/2018/912500a139/17D45VsBU1x",
"parentPublication": {
"id": "proceedings/icbk/2018/9125/0",
"title": "2018 IEEE International Conference on Big Knowledge (ICBK)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09908148",
"title": "GenoREC: A Recommendation System for Interactive Genomics Data Visualization",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09908148/1Hbaqe3xebS",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/03/08834822",
"title": "Integral Curve Clustering and Simplification for Flow Visualization: A Comparative Evaluation",
"doi": null,
"abstractUrl": "/journal/tg/2021/03/08834822/1dgv8seoz5u",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/big-data/2020/6251/0/09378261",
"title": "Inventory Based Recommendation Algorithms",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2020/09378261/1s64cbHE8Ao",
"parentPublication": {
"id": "proceedings/big-data/2020/6251/0",
"title": "2020 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icicas/2020/9085/0/908500a377",
"title": "Comparing Recommendation Algorithms in Session-based E-commerce Sites",
"doi": null,
"abstractUrl": "/proceedings-article/icicas/2020/908500a377/1sZ2XiIUKw8",
"parentPublication": {
"id": "proceedings/icicas/2020/9085/0",
"title": "2020 International Conference on Intelligent Computing, Automation and Systems (ICICAS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/12/09444894",
"title": "Deconstructing Categorization in Visualization Recommendation: A Taxonomy and Comparative Study",
"doi": null,
"abstractUrl": "/journal/tg/2022/12/09444894/1u51xYbTfmU",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/12/09524484",
"title": "GEViTRec: Data Reconnaissance Through Recommendation Using a Domain-Specific Visualization Prevalence Design Space",
"doi": null,
"abstractUrl": "/journal/tg/2022/12/09524484/1wpqlzOa8G4",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552902",
"articleId": "1xic4qsF8zK",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552899",
"articleId": "1xicaOuuM8w",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xicaOuuM8w",
"doi": "10.1109/TVCG.2021.3114866",
"abstract": "Model checkers provide algorithms for proving that a mathematical model of a system satisfies a given specification. In case of a violation, a counterexample that shows the erroneous behavior is returned. Understanding these counterexamples is challenging, especially for hyperproperty specifications, i.e., specifications that relate multiple executions of a system to each other. We aim to facilitate the visual analysis of such counterexamples through our H<sc>yper</sc>V<sc>is</sc> tool, which provides interactive visualizations of the given model, specification, and counterexample. Within an iterative and interdisciplinary design process, we developed visualization solutions that can effectively communicate the core aspects of the model checking result. Specifically, we introduce graphical representations of binary values for improving pattern recognition, color encoding for better indicating related aspects, visually enhanced textual descriptions, as well as extensive cross-view highlighting mechanisms. Further, through an underlying causal analysis of the counterexample, we are also able to identify values that contributed to the violation and use this knowledge for both improved encoding and highlighting. Finally, the analyst can modify both the specification of the hyperproperty and the system directly within H<sc>yper</sc>V<sc>is</sc> and initiate the model checking of the new version. In combination, these features notably support the analyst in understanding the error leading to the counterexample as well as iterating the provided system and specification. We ran multiple case studies with H<sc>yper</sc>V<sc>is</sc> and tested it with domain experts in qualitative feedback sessions. The participants' positive feedback confirms the considerable improvement over the manual, text-based status quo and the value of the tool for explaining hyperproperties.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Model checkers provide algorithms for proving that a mathematical model of a system satisfies a given specification. In case of a violation, a counterexample that shows the erroneous behavior is returned. Understanding these counterexamples is challenging, especially for hyperproperty specifications, i.e., specifications that relate multiple executions of a system to each other. We aim to facilitate the visual analysis of such counterexamples through our H<sc>yper</sc>V<sc>is</sc> tool, which provides interactive visualizations of the given model, specification, and counterexample. Within an iterative and interdisciplinary design process, we developed visualization solutions that can effectively communicate the core aspects of the model checking result. Specifically, we introduce graphical representations of binary values for improving pattern recognition, color encoding for better indicating related aspects, visually enhanced textual descriptions, as well as extensive cross-view highlighting mechanisms. Further, through an underlying causal analysis of the counterexample, we are also able to identify values that contributed to the violation and use this knowledge for both improved encoding and highlighting. Finally, the analyst can modify both the specification of the hyperproperty and the system directly within H<sc>yper</sc>V<sc>is</sc> and initiate the model checking of the new version. In combination, these features notably support the analyst in understanding the error leading to the counterexample as well as iterating the provided system and specification. We ran multiple case studies with H<sc>yper</sc>V<sc>is</sc> and tested it with domain experts in qualitative feedback sessions. The participants' positive feedback confirms the considerable improvement over the manual, text-based status quo and the value of the tool for explaining hyperproperties.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Model checkers provide algorithms for proving that a mathematical model of a system satisfies a given specification. In case of a violation, a counterexample that shows the erroneous behavior is returned. Understanding these counterexamples is challenging, especially for hyperproperty specifications, i.e., specifications that relate multiple executions of a system to each other. We aim to facilitate the visual analysis of such counterexamples through our HyperVis tool, which provides interactive visualizations of the given model, specification, and counterexample. Within an iterative and interdisciplinary design process, we developed visualization solutions that can effectively communicate the core aspects of the model checking result. Specifically, we introduce graphical representations of binary values for improving pattern recognition, color encoding for better indicating related aspects, visually enhanced textual descriptions, as well as extensive cross-view highlighting mechanisms. Further, through an underlying causal analysis of the counterexample, we are also able to identify values that contributed to the violation and use this knowledge for both improved encoding and highlighting. Finally, the analyst can modify both the specification of the hyperproperty and the system directly within HyperVis and initiate the model checking of the new version. In combination, these features notably support the analyst in understanding the error leading to the counterexample as well as iterating the provided system and specification. We ran multiple case studies with HyperVis and tested it with domain experts in qualitative feedback sessions. The participants' positive feedback confirms the considerable improvement over the manual, text-based status quo and the value of the tool for explaining hyperproperties.",
"title": "Visual Analysis of Hyperproperties for Understanding Model Checking Results",
"normalizedTitle": "Visual Analysis of Hyperproperties for Understanding Model Checking Results",
"fno": "09552899",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Model Checking",
"Visualization",
"Integrated Circuit Modeling",
"Tools",
"Computational Modeling",
"Encoding",
"Process Control",
"Analyzing Counterexamples",
"Hyperproperties",
"Multiple Coordinate Views",
"Explainable Formal Methods"
],
"authors": [
{
"givenName": "Tom",
"surname": "Horak",
"fullName": "Tom Horak",
"affiliation": "Interactive Media Lab at Technische Universität Dresden, Germany",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Norine",
"surname": "Coenen",
"fullName": "Norine Coenen",
"affiliation": "Reactive Systems Group at CISPA Helmholtz Center for Information Security, Germany",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Niklas",
"surname": "Metzger",
"fullName": "Niklas Metzger",
"affiliation": "Reactive Systems Group at CISPA Helmholtz Center for Information Security, Germany",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Christopher",
"surname": "Hahn",
"fullName": "Christopher Hahn",
"affiliation": "Reactive Systems Group at CISPA Helmholtz Center for Information Security, Germany",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Tamara",
"surname": "Flemisch",
"fullName": "Tamara Flemisch",
"affiliation": "Interactive Media Lab at Technische Universität Dresden, Germany",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Julián",
"surname": "Méndez",
"fullName": "Julián Méndez",
"affiliation": "Interactive Media Lab at Technische Universität Dresden, Germany",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Dennis",
"surname": "Dimov",
"fullName": "Dennis Dimov",
"affiliation": "Interactive Media Lab at Technische Universität Dresden, Germany",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Bernd",
"surname": "Finkbeiner",
"fullName": "Bernd Finkbeiner",
"affiliation": "Reactive Systems Group at CISPA Helmholtz Center for Information Security, Germany",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Raimund",
"surname": "Dachselt",
"fullName": "Raimund Dachselt",
"affiliation": "Interactive Media Lab, the Centre for Tactile Internet (CeTI), and the Cluster of Excellence Physics of Life (PoL) at Technische Universität Dresden, Germany",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "357-367",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/lics/2002/1483/0/14830019",
"title": "Tree-Like Counterexamples in Model Checking",
"doi": null,
"abstractUrl": "/proceedings-article/lics/2002/14830019/12OmNqBKU1N",
"parentPublication": {
"id": "proceedings/lics/2002/1483/0",
"title": "Proceedings 17th Annual IEEE Symposium on Logic in Computer Science",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/apsec/2013/2144/2/2144b134",
"title": "A Practical Study of Debugging Using Model Checking",
"doi": null,
"abstractUrl": "/proceedings-article/apsec/2013/2144b134/12OmNxA3Z6a",
"parentPublication": {
"id": "apsec/2013/2144/2",
"title": "2013 20th Asia-Pacific Software Engineering Conference (APSEC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icfem/1998/9198/0/91980046",
"title": "Using Model Checking to Generate Tests from Specifications",
"doi": null,
"abstractUrl": "/proceedings-article/icfem/1998/91980046/12OmNxzuMHi",
"parentPublication": {
"id": "proceedings/icfem/1998/9198/0",
"title": "Formal Engineering Methods, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icse/2013/3073/0/06606566",
"title": "Detecting spurious counterexamples efficiently in abstract model checking",
"doi": null,
"abstractUrl": "/proceedings-article/icse/2013/06606566/12OmNzsrwpc",
"parentPublication": {
"id": "proceedings/icse/2013/3073/0",
"title": "2013 35th International Conference on Software Engineering (ICSE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/ts/2014/12/06895263",
"title": "Making CEGAR More Efficient in Software Model Checking",
"doi": null,
"abstractUrl": "/journal/ts/2014/12/06895263/13rRUx0xQ1f",
"parentPublication": {
"id": "trans/ts",
"title": "IEEE Transactions on Software Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tc/2011/05/ttc2011050734",
"title": "Counterexample-Guided Assume-Guarantee Synthesis through Learning",
"doi": null,
"abstractUrl": "/journal/tc/2011/05/ttc2011050734/13rRUxC0SVs",
"parentPublication": {
"id": "trans/tc",
"title": "IEEE Transactions on Computers",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/ts/2009/02/tts2009020241",
"title": "Counterexample Generation in Probabilistic Model Checking",
"doi": null,
"abstractUrl": "/journal/ts/2009/02/tts2009020241/13rRUyeCkbZ",
"parentPublication": {
"id": "trans/ts",
"title": "IEEE Transactions on Software Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/ts/2021/06/08708934",
"title": "Debugging of Behavioural Models using Counterexample Analysis",
"doi": null,
"abstractUrl": "/journal/ts/2021/06/08708934/19Q3oSkS2je",
"parentPublication": {
"id": "trans/ts",
"title": "IEEE Transactions on Software Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ase/2019/2508/0/250800a565",
"title": "Model Checking Embedded Control Software using OS-in-the-Loop CEGAR",
"doi": null,
"abstractUrl": "/proceedings-article/ase/2019/250800a565/1gysWnvE26Q",
"parentPublication": {
"id": "proceedings/ase/2019/2508/0",
"title": "2019 34th IEEE/ACM International Conference on Automated Software Engineering (ASE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iceccs/2020/8558/0/855800a001",
"title": "Visual counterexample explanation for model checking with OERITTE",
"doi": null,
"abstractUrl": "/proceedings-article/iceccs/2020/855800a001/1s658RjsOoU",
"parentPublication": {
"id": "proceedings/iceccs/2020/8558/0",
"title": "2020 25th International Conference on Engineering of Complex Computer Systems (ICECCS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552925",
"articleId": "1xibWnPGM5a",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552229",
"articleId": "1xic387kwVy",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBb8EDAi7S",
"name": "ttg202201-09552899s1-supp1-3114866.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552899s1-supp1-3114866.mp4",
"extension": "mp4",
"size": "45.3 MB",
"__typename": "WebExtraType"
},
{
"id": "1zBb8qPcuHe",
"name": "ttg202201-09552899s1-supp2-3114866.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552899s1-supp2-3114866.pdf",
"extension": "pdf",
"size": "1.31 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xic387kwVy",
"doi": "10.1109/TVCG.2021.3114850",
"abstract": "Graph mining is an essential component of recommender systems and search engines. Outputs of graph mining models typically provide a ranked list sorted by each item's relevance or utility. However, recent research has identified issues of algorithmic bias in such models, and new graph mining algorithms have been proposed to correct for bias. As such, algorithm developers need tools that can help them uncover potential biases in their models while also exploring the impacts of correcting for biases when employing fairness-aware algorithms. In this paper, we present FairRankVis, a visual analytics framework designed to enable the exploration of multi-class bias in graph mining algorithms. We support both group and individual fairness levels of comparison. Our framework is designed to enable model developers to compare multi-class fairness between algorithms (for example, comparing PageRank with a debiased PageRank algorithm) to assess the impacts of algorithmic debiasing with respect to group and individual fairness. We demonstrate our framework through two usage scenarios inspecting algorithmic fairness.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Graph mining is an essential component of recommender systems and search engines. Outputs of graph mining models typically provide a ranked list sorted by each item's relevance or utility. However, recent research has identified issues of algorithmic bias in such models, and new graph mining algorithms have been proposed to correct for bias. As such, algorithm developers need tools that can help them uncover potential biases in their models while also exploring the impacts of correcting for biases when employing fairness-aware algorithms. In this paper, we present FairRankVis, a visual analytics framework designed to enable the exploration of multi-class bias in graph mining algorithms. We support both group and individual fairness levels of comparison. Our framework is designed to enable model developers to compare multi-class fairness between algorithms (for example, comparing PageRank with a debiased PageRank algorithm) to assess the impacts of algorithmic debiasing with respect to group and individual fairness. We demonstrate our framework through two usage scenarios inspecting algorithmic fairness.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Graph mining is an essential component of recommender systems and search engines. Outputs of graph mining models typically provide a ranked list sorted by each item's relevance or utility. However, recent research has identified issues of algorithmic bias in such models, and new graph mining algorithms have been proposed to correct for bias. As such, algorithm developers need tools that can help them uncover potential biases in their models while also exploring the impacts of correcting for biases when employing fairness-aware algorithms. In this paper, we present FairRankVis, a visual analytics framework designed to enable the exploration of multi-class bias in graph mining algorithms. We support both group and individual fairness levels of comparison. Our framework is designed to enable model developers to compare multi-class fairness between algorithms (for example, comparing PageRank with a debiased PageRank algorithm) to assess the impacts of algorithmic debiasing with respect to group and individual fairness. We demonstrate our framework through two usage scenarios inspecting algorithmic fairness.",
"title": "FairRankVis: A Visual Analytics Framework for Exploring Algorithmic Fairness in Graph Mining Models",
"normalizedTitle": "FairRankVis: A Visual Analytics Framework for Exploring Algorithmic Fairness in Graph Mining Models",
"fno": "09552229",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Analytical Models",
"Visual Analytics",
"Machine Learning Algorithms",
"Task Analysis",
"Data Mining",
"Data Models",
"Machine Learning",
"Graph Ranking",
"Fairness",
"Visual Analytics"
],
"authors": [
{
"givenName": "Tiankai",
"surname": "Xie",
"fullName": "Tiankai Xie",
"affiliation": "Arizona State University, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yuxin",
"surname": "Ma",
"fullName": "Yuxin Ma",
"affiliation": "Southern University of Science and Technology, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jian",
"surname": "Kang",
"fullName": "Jian Kang",
"affiliation": "University of Illinois at Urbana-Champaign, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Hanghang",
"surname": "Tong",
"fullName": "Hanghang Tong",
"affiliation": "University of Illinois at Urbana-Champaign, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Ross",
"surname": "Maciejewski",
"fullName": "Ross Maciejewski",
"affiliation": "Arizona State University, United States",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "368-377",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "mags/sp/2018/03/msp2018030034",
"title": "A Harm-Reduction Framework for Algorithmic Fairness",
"doi": null,
"abstractUrl": "/magazine/sp/2018/03/msp2018030034/13rRUwI5TW0",
"parentPublication": {
"id": "mags/sp",
"title": "IEEE Security & Privacy",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdmw/2018/9288/0/928800b062",
"title": "Hubness as a Case of Technical Algorithmic Bias in Music Recommendation",
"doi": null,
"abstractUrl": "/proceedings-article/icdmw/2018/928800b062/18jXA8K5fLG",
"parentPublication": {
"id": "proceedings/icdmw/2018/9288/0",
"title": "2018 IEEE International Conference on Data Mining Workshops (ICDMW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacvw/2022/5824/0/582400a410",
"title": "Algorithmic Fairness in Face Morphing Attack Detection",
"doi": null,
"abstractUrl": "/proceedings-article/wacvw/2022/582400a410/1B12r8N8LMk",
"parentPublication": {
"id": "proceedings/wacvw/2022/5824/0",
"title": "2022 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icstw/2022/9628/0/962800a094",
"title": "A Combinatorial Approach to Fairness Testing of Machine Learning Models",
"doi": null,
"abstractUrl": "/proceedings-article/icstw/2022/962800a094/1E2wsmd5wn6",
"parentPublication": {
"id": "proceedings/icstw/2022/9628/0",
"title": "2022 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/trex/2022/9356/0/935600a001",
"title": "How Do Algorithmic Fairness Metrics Align with Human Judgement? A Mixed-Initiative System for Contextualized Fairness Assessment",
"doi": null,
"abstractUrl": "/proceedings-article/trex/2022/935600a001/1J9BkYzzrHi",
"parentPublication": {
"id": "proceedings/trex/2022/9356/0",
"title": "2022 IEEE Workshop on TRust and EXpertise in Visual Analytics (TREX)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vds/2022/5721/0/572100a027",
"title": "BiaScope: Visual Unfairness Diagnosis for Graph Embeddings",
"doi": null,
"abstractUrl": "/proceedings-article/vds/2022/572100a027/1JezJPxSJHy",
"parentPublication": {
"id": "proceedings/vds/2022/5721/0",
"title": "2022 IEEE Visualization in Data Science (VDS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/5555/01/10097603",
"title": "Fairness in Graph Mining: A Survey",
"doi": null,
"abstractUrl": "/journal/tk/5555/01/10097603/1M9lHGqR5oA",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdm/2020/8316/0/831600a182",
"title": "Metric-Free Individual Fairness with Cooperative Contextual Bandits",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2020/831600a182/1r54IOsHM0o",
"parentPublication": {
"id": "proceedings/icdm/2020/8316/0",
"title": "2020 IEEE International Conference on Data Mining (ICDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/big-data/2020/6251/0/09377894",
"title": "BeFair: Addressing Fairness in the Banking Sector",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2020/09377894/1s64OBfBrwI",
"parentPublication": {
"id": "proceedings/big-data/2020/6251/0",
"title": "2020 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/euros&p/2021/1491/0/149100a292",
"title": "On the Privacy Risks of Algorithmic Fairness",
"doi": null,
"abstractUrl": "/proceedings-article/euros&p/2021/149100a292/1yg1gS8yxq0",
"parentPublication": {
"id": "proceedings/euros&p/2021/1491/0",
"title": "2021 IEEE European Symposium on Security and Privacy (EuroS&P)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552899",
"articleId": "1xicaOuuM8w",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09555810",
"articleId": "1xlw2uJhEXe",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xlw2uJhEXe",
"doi": "10.1109/TVCG.2021.3114836",
"abstract": "Machine learning (ML) is increasingly applied to Electronic Health Records (EHRs) to solve clinical prediction tasks. Although many ML models perform promisingly, issues with model transparency and interpretability limit their adoption in clinical practice. Directly using existing explainable ML techniques in clinical settings can be challenging. Through literature surveys and collaborations with six clinicians with an average of 17 years of clinical experience, we identified three key challenges, including clinicians' unfamiliarity with ML features, lack of contextual information, and the need for cohort-level evidence. Following an iterative design process, we further designed and developed VBridge, a visual analytics tool that seamlessly incorporates ML explanations into clinicians' decision-making workflow. The system includes a novel hierarchical display of contribution-based feature explanations and enriched interactions that <italic>connect the dots</italic> between ML features, explanations, and data. We demonstrated the effectiveness of VBridge through two case studies and expert interviews with four clinicians, showing that visually associating model explanations with patients' situational records can help clinicians better interpret and use model predictions when making clinician decisions. We further derived a list of design implications for developing future explainable ML tools to support clinical decision-making.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Machine learning (ML) is increasingly applied to Electronic Health Records (EHRs) to solve clinical prediction tasks. Although many ML models perform promisingly, issues with model transparency and interpretability limit their adoption in clinical practice. Directly using existing explainable ML techniques in clinical settings can be challenging. Through literature surveys and collaborations with six clinicians with an average of 17 years of clinical experience, we identified three key challenges, including clinicians' unfamiliarity with ML features, lack of contextual information, and the need for cohort-level evidence. Following an iterative design process, we further designed and developed VBridge, a visual analytics tool that seamlessly incorporates ML explanations into clinicians' decision-making workflow. The system includes a novel hierarchical display of contribution-based feature explanations and enriched interactions that <italic>connect the dots</italic> between ML features, explanations, and data. We demonstrated the effectiveness of VBridge through two case studies and expert interviews with four clinicians, showing that visually associating model explanations with patients' situational records can help clinicians better interpret and use model predictions when making clinician decisions. We further derived a list of design implications for developing future explainable ML tools to support clinical decision-making.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Machine learning (ML) is increasingly applied to Electronic Health Records (EHRs) to solve clinical prediction tasks. Although many ML models perform promisingly, issues with model transparency and interpretability limit their adoption in clinical practice. Directly using existing explainable ML techniques in clinical settings can be challenging. Through literature surveys and collaborations with six clinicians with an average of 17 years of clinical experience, we identified three key challenges, including clinicians' unfamiliarity with ML features, lack of contextual information, and the need for cohort-level evidence. Following an iterative design process, we further designed and developed VBridge, a visual analytics tool that seamlessly incorporates ML explanations into clinicians' decision-making workflow. The system includes a novel hierarchical display of contribution-based feature explanations and enriched interactions that connect the dots between ML features, explanations, and data. We demonstrated the effectiveness of VBridge through two case studies and expert interviews with four clinicians, showing that visually associating model explanations with patients' situational records can help clinicians better interpret and use model predictions when making clinician decisions. We further derived a list of design implications for developing future explainable ML tools to support clinical decision-making.",
"title": "VBridge: Connecting the Dots Between Features and Data to Explain Healthcare Models",
"normalizedTitle": "VBridge: Connecting the Dots Between Features and Data to Explain Healthcare Models",
"fno": "09555810",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Predictive Models",
"Decision Making",
"Tools",
"Computational Modeling",
"Visual Analytics",
"Hospitals",
"Task Analysis",
"Explainable Artificial Intelligence",
"Healthcare",
"Visual Analytics",
"Decision Making"
],
"authors": [
{
"givenName": "Furui",
"surname": "Cheng",
"fullName": "Furui Cheng",
"affiliation": "Hong Kong University of Science and Technology, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Dongyu",
"surname": "Liu",
"fullName": "Dongyu Liu",
"affiliation": "Massachusetts Institute of Technology, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Fan",
"surname": "Du",
"fullName": "Fan Du",
"affiliation": "Adobe Research, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yanna",
"surname": "Lin",
"fullName": "Yanna Lin",
"affiliation": "Hong Kong University of Science and Technology, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Alexandra",
"surname": "Zytek",
"fullName": "Alexandra Zytek",
"affiliation": "Massachusetts Institute of Technology, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Haomin",
"surname": "Li",
"fullName": "Haomin Li",
"affiliation": "Children's Hospital of Zhejiang University School of Medicine, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Huamin",
"surname": "Qu",
"fullName": "Huamin Qu",
"affiliation": "Hong Kong University of Science and Technology, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Kalyan",
"surname": "Veeramachaneni",
"fullName": "Kalyan Veeramachaneni",
"affiliation": "Massachusetts Institute of Technology, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "378-388",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "trans/tg/2019/03/08304678",
"title": "KAVAGait: Knowledge-Assisted Visual Analytics for Clinical Gait Analysis",
"doi": null,
"abstractUrl": "/journal/tg/2019/03/08304678/17D45WaTkk5",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vast/2009/5283/0/05333023",
"title": "Connecting the dots in visual analysis",
"doi": null,
"abstractUrl": "/proceedings-article/vast/2009/05333023/1HJyHYJk7eg",
"parentPublication": {
"id": "proceedings/vast/2009/5283/0",
"title": "2009 IEEE Symposium on Visual Analytics Science and Technology",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/ai/5555/01/09971460",
"title": "User-Centric Explainability in Healthcare: A Knowledge-Level Perspective of Informed Machine Learning",
"doi": null,
"abstractUrl": "/journal/ai/5555/01/09971460/1ISVU8Rd528",
"parentPublication": {
"id": "trans/ai",
"title": "IEEE Transactions on Artificial Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/e-science/2022/6124/0/612400a431",
"title": "PiMS: A Pre-ML Labelling Tool",
"doi": null,
"abstractUrl": "/proceedings-article/e-science/2022/612400a431/1J6hpa8Fh8k",
"parentPublication": {
"id": "proceedings/e-science/2022/6124/0",
"title": "2022 IEEE 18th International Conference on e-Science (e-Science)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/trex/2022/9356/0/935600a008",
"title": "Trustworthy Visual Analytics in Clinical Gait Analysis: A Case Study for Patients with Cerebral Palsy",
"doi": null,
"abstractUrl": "/proceedings-article/trex/2022/935600a008/1J9BkDHcAz6",
"parentPublication": {
"id": "proceedings/trex/2022/9356/0",
"title": "2022 IEEE Workshop on TRust and EXpertise in Visual Analytics (TREX)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vahc/2022/0103/0/10108523",
"title": "Evaluation of Data Visualizations for an Electronic Patient Preferences Tool for Older Adults Diagnosed with Hematologic Malignancies",
"doi": null,
"abstractUrl": "/proceedings-article/vahc/2022/10108523/1MIgSlSuYw0",
"parentPublication": {
"id": "proceedings/vahc/2022/0103/0",
"title": "2022 Workshop on Visual Analytics in Healthcare (VAHC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bracis/2019/4253/0/425300a467",
"title": "Argumentation-Based Agents that Explain Their Decisions",
"doi": null,
"abstractUrl": "/proceedings-article/bracis/2019/425300a467/1fHkH71PDFu",
"parentPublication": {
"id": "proceedings/bracis/2019/4253/0",
"title": "2019 8th Brazilian Conference on Intelligent Systems (BRACIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2019/1867/0/08983360",
"title": "Patient Activity Monitoring Based on Real-Time Location Data",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2019/08983360/1hguccNTnfG",
"parentPublication": {
"id": "proceedings/bibm/2019/1867/0",
"title": "2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ichi/2020/5382/0/09374365",
"title": "Machine Learning Based Clinical Decision Support and Clinician Trust",
"doi": null,
"abstractUrl": "/proceedings-article/ichi/2020/09374365/1rUIXSTum4M",
"parentPublication": {
"id": "proceedings/ichi/2020/5382/0",
"title": "2020 IEEE International Conference on Healthcare Informatics (ICHI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/trex/2021/1817/0/181700a052",
"title": "How to deal with Uncertainty in Machine Learning for Medical Imaging?",
"doi": null,
"abstractUrl": "/proceedings-article/trex/2021/181700a052/1yQB6pOqNNK",
"parentPublication": {
"id": "proceedings/trex/2021/1817/0",
"title": "2021 IEEE Workshop on TRust and EXpertise in Visual Analytics (TREX)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552229",
"articleId": "1xic387kwVy",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552906",
"articleId": "1xic46x3fmU",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBb0CGCySQ",
"name": "ttg202201-09555810s1-supp2-3114836.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09555810s1-supp2-3114836.pdf",
"extension": "pdf",
"size": "437 kB",
"__typename": "WebExtraType"
},
{
"id": "1zBb0ITwDgk",
"name": "ttg202201-09555810s1-supp1-3114836.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09555810s1-supp1-3114836.mp4",
"extension": "mp4",
"size": "14.2 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xic46x3fmU",
"doi": "10.1109/TVCG.2021.3114792",
"abstract": "We introduce Diatoms, a technique that generates design inspiration for glyphs by sampling from palettes of mark shapes, encoding channels, and glyph scaffold shapes. Diatoms allows for a degree of randomness while respecting constraints imposed by columns in a data table: their data types and domains as well as semantic associations between columns as specified by the designer. We pair this generative design process with two forms of interactive design externalization that enable comparison and critique of the design alternatives. First, we incorporate a familiar <italic>small multiples</italic> configuration in which every data point is drawn according to a single glyph design, coupled with the ability to page between alternative glyph designs. Second, we propose a <italic>small permutables</italic> design gallery, in which a single data point is drawn according to each alternative glyph design, coupled with the ability to page between data points. We demonstrate an implementation of our technique as an extension to Tableau featuring three example palettes, and to better understand how Diatoms could fit into existing design workflows, we conducted interviews and chauffeured demos with 12 designers. Finally, we reflect on our process and the designers' reactions, discussing the potential of our technique in the context of visualization authoring systems. Ultimately, our approach to glyph design and comparison can kickstart and inspire visualization design, allowing for the serendipitous discovery of shape and channel combinations that would have otherwise been overlooked.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We introduce Diatoms, a technique that generates design inspiration for glyphs by sampling from palettes of mark shapes, encoding channels, and glyph scaffold shapes. Diatoms allows for a degree of randomness while respecting constraints imposed by columns in a data table: their data types and domains as well as semantic associations between columns as specified by the designer. We pair this generative design process with two forms of interactive design externalization that enable comparison and critique of the design alternatives. First, we incorporate a familiar <italic>small multiples</italic> configuration in which every data point is drawn according to a single glyph design, coupled with the ability to page between alternative glyph designs. Second, we propose a <italic>small permutables</italic> design gallery, in which a single data point is drawn according to each alternative glyph design, coupled with the ability to page between data points. We demonstrate an implementation of our technique as an extension to Tableau featuring three example palettes, and to better understand how Diatoms could fit into existing design workflows, we conducted interviews and chauffeured demos with 12 designers. Finally, we reflect on our process and the designers' reactions, discussing the potential of our technique in the context of visualization authoring systems. Ultimately, our approach to glyph design and comparison can kickstart and inspire visualization design, allowing for the serendipitous discovery of shape and channel combinations that would have otherwise been overlooked.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We introduce Diatoms, a technique that generates design inspiration for glyphs by sampling from palettes of mark shapes, encoding channels, and glyph scaffold shapes. Diatoms allows for a degree of randomness while respecting constraints imposed by columns in a data table: their data types and domains as well as semantic associations between columns as specified by the designer. We pair this generative design process with two forms of interactive design externalization that enable comparison and critique of the design alternatives. First, we incorporate a familiar small multiples configuration in which every data point is drawn according to a single glyph design, coupled with the ability to page between alternative glyph designs. Second, we propose a small permutables design gallery, in which a single data point is drawn according to each alternative glyph design, coupled with the ability to page between data points. We demonstrate an implementation of our technique as an extension to Tableau featuring three example palettes, and to better understand how Diatoms could fit into existing design workflows, we conducted interviews and chauffeured demos with 12 designers. Finally, we reflect on our process and the designers' reactions, discussing the potential of our technique in the context of visualization authoring systems. Ultimately, our approach to glyph design and comparison can kickstart and inspire visualization design, allowing for the serendipitous discovery of shape and channel combinations that would have otherwise been overlooked.",
"title": "Generative Design Inspiration for Glyphs with Diatoms",
"normalizedTitle": "Generative Design Inspiration for Glyphs with Diatoms",
"fno": "09552906",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Data Visualization",
"Visualization",
"Shape",
"Tools",
"Encoding",
"Media",
"Authoring Systems",
"Glyphs",
"Multidimensional Data",
"Generative Design",
"Communicative Visualization",
"Small Multiples",
"Qualitative Evaluation"
],
"authors": [
{
"givenName": "Matthew",
"surname": "Brehmer",
"fullName": "Matthew Brehmer",
"affiliation": "Tableau Research, Canada",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Robert",
"surname": "Kosara",
"fullName": "Robert Kosara",
"affiliation": "Tableau Research, Canada",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Carmen",
"surname": "Hull",
"fullName": "Carmen Hull",
"affiliation": "University of Calgary, Canada",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": false,
"showRecommendedArticles": true,
"isOpenAccess": true,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "389-399",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "trans/tg/2017/07/07445239",
"title": "A Systematic Review of Experimental Studies on Data Glyphs",
"doi": null,
"abstractUrl": "/journal/tg/2017/07/07445239/13rRUNvgz4m",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2014/12/06875973",
"title": "The Influence of Contour on Similarity Perception of Star Glyphs",
"doi": null,
"abstractUrl": "/journal/tg/2014/12/06875973/13rRUwhHcQV",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2011/12/ttg2011121949",
"title": "Flow Radar Glyphs—Static Visualization of Unsteady Flow with Uncertainty",
"doi": null,
"abstractUrl": "/journal/tg/2011/12/ttg2011121949/13rRUxC0SOU",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2013/08/ttg2013081331",
"title": "Representing Flow Patterns by Using Streamlines with Glyphs",
"doi": null,
"abstractUrl": "/journal/tg/2013/08/ttg2013081331/13rRUxly9dT",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2018/7202/0/720200a058",
"title": "Visualizing Multidimensional Data in Treemaps with Adaptive Glyphs",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2018/720200a058/17D45XeKgvR",
"parentPublication": {
"id": "proceedings/iv/2018/7202/0",
"title": "2018 22nd International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09906974",
"title": "MetaGlyph: Automatic Generation of Metaphoric Glyph-based Visualization",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09906974/1H5EXDBdLz2",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2019/2838/0/283800a157",
"title": "Evaluation of Effectiveness of Glyphs to Enhance ChronoView",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2019/283800a157/1cMF9mvWMFO",
"parentPublication": {
"id": "proceedings/iv/2019/2838/0",
"title": "2019 23rd International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2020/04/08967136",
"title": "Glyphboard: Visual Exploration of High-Dimensional Data Combining Glyphs with Dimensionality Reduction",
"doi": null,
"abstractUrl": "/journal/tg/2020/04/08967136/1gPjxXgWQM0",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/09/09067088",
"title": "AgentVis: Visual Analysis of Agent Behavior With Hierarchical Glyphs",
"doi": null,
"abstractUrl": "/journal/tg/2021/09/09067088/1j1lyTz50k0",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/01/09557223",
"title": "GlyphCreator: Towards Example-based Automatic Generation of Circular Glyphs",
"doi": null,
"abstractUrl": "/journal/tg/2022/01/09557223/1xlvZajdjmo",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09555810",
"articleId": "1xlw2uJhEXe",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09557223",
"articleId": "1xlvZajdjmo",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBaNnSVzag",
"name": "ttg202201-09552906s1-supp1-3114792.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552906s1-supp1-3114792.mp4",
"extension": "mp4",
"size": "67.5 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xlvZajdjmo",
"doi": "10.1109/TVCG.2021.3114877",
"abstract": "Circular glyphs are used across disparate fields to represent multidimensional data. However, although these glyphs are extremely effective, creating them is often laborious, even for those with professional design skills. This paper presents GlyphCreator, an interactive tool for the example-based generation of circular glyphs. Given an example circular glyph and multidimensional input data, GlyphCreator promptly generates a list of design candidates, any of which can be edited to satisfy the requirements of a particular representation. To develop GlyphCreator, we first derive a design space of circular glyphs by summarizing relationships between different visual elements. With this design space, we build a circular glyph dataset and develop a deep learning model for glyph parsing. The model can deconstruct a circular glyph bitmap into a series of visual elements. Next, we introduce an interface that helps users bind the input data attributes to visual elements and customize visual styles. We evaluate the parsing model through a quantitative experiment, demonstrate the use of GlyphCreator through two use scenarios, and validate its effectiveness through user interviews.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Circular glyphs are used across disparate fields to represent multidimensional data. However, although these glyphs are extremely effective, creating them is often laborious, even for those with professional design skills. This paper presents GlyphCreator, an interactive tool for the example-based generation of circular glyphs. Given an example circular glyph and multidimensional input data, GlyphCreator promptly generates a list of design candidates, any of which can be edited to satisfy the requirements of a particular representation. To develop GlyphCreator, we first derive a design space of circular glyphs by summarizing relationships between different visual elements. With this design space, we build a circular glyph dataset and develop a deep learning model for glyph parsing. The model can deconstruct a circular glyph bitmap into a series of visual elements. Next, we introduce an interface that helps users bind the input data attributes to visual elements and customize visual styles. We evaluate the parsing model through a quantitative experiment, demonstrate the use of GlyphCreator through two use scenarios, and validate its effectiveness through user interviews.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Circular glyphs are used across disparate fields to represent multidimensional data. However, although these glyphs are extremely effective, creating them is often laborious, even for those with professional design skills. This paper presents GlyphCreator, an interactive tool for the example-based generation of circular glyphs. Given an example circular glyph and multidimensional input data, GlyphCreator promptly generates a list of design candidates, any of which can be edited to satisfy the requirements of a particular representation. To develop GlyphCreator, we first derive a design space of circular glyphs by summarizing relationships between different visual elements. With this design space, we build a circular glyph dataset and develop a deep learning model for glyph parsing. The model can deconstruct a circular glyph bitmap into a series of visual elements. Next, we introduce an interface that helps users bind the input data attributes to visual elements and customize visual styles. We evaluate the parsing model through a quantitative experiment, demonstrate the use of GlyphCreator through two use scenarios, and validate its effectiveness through user interviews.",
"title": "GlyphCreator: Towards Example-based Automatic Generation of Circular Glyphs",
"normalizedTitle": "GlyphCreator: Towards Example-based Automatic Generation of Circular Glyphs",
"fno": "09557223",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Data Visualization",
"Visualization",
"Layout",
"Deep Learning",
"Data Mining",
"Tools",
"Task Analysis",
"Glyph Based Visualization",
"Machine Learning",
"Automatic Visualization"
],
"authors": [
{
"givenName": "Lu",
"surname": "Ying",
"fullName": "Lu Ying",
"affiliation": "State Key Lab of CAD & CG, Zhejiang University, Hangzhou, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Tan",
"surname": "Tangl",
"fullName": "Tan Tangl",
"affiliation": "State Key Lab of CAD & CG, Zhejiang University, Hangzhou, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yuzhe",
"surname": "Luo",
"fullName": "Yuzhe Luo",
"affiliation": "State Key Lab of CAD & CG, Zhejiang University, Hangzhou, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Lvkeshen",
"surname": "Shen",
"fullName": "Lvkeshen Shen",
"affiliation": "State Key Lab of CAD & CG, Zhejiang University, Hangzhou, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Xiao",
"surname": "Xie",
"fullName": "Xiao Xie",
"affiliation": "Department of Sport Science, Zhejiang University, Hangrhou, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Lingyun",
"surname": "Yu",
"fullName": "Lingyun Yu",
"affiliation": "Department of Computing, Xi'an Jiaotong-Liverpool University, Suzhou, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yingcai",
"surname": "Wu",
"fullName": "Yingcai Wu",
"affiliation": "State Key Lab of CAD & CG, Zhejiang University, Hangzhou, China",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "400-410",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/scivis/2015/9785/0/07429504",
"title": "3D superquadric glyphs for visualizing myocardial motion",
"doi": null,
"abstractUrl": "/proceedings-article/scivis/2015/07429504/12OmNrIaemh",
"parentPublication": {
"id": "proceedings/scivis/2015/9785/0",
"title": "2015 IEEE Scientific Visualization Conference (SciVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pacificvis/2014/2874/0/2874a017",
"title": "Non-overlapping Aggregated Multivariate Glyphs for Moving Objects",
"doi": null,
"abstractUrl": "/proceedings-article/pacificvis/2014/2874a017/12OmNy2agTd",
"parentPublication": {
"id": "proceedings/pacificvis/2014/2874/0",
"title": "2014 IEEE Pacific Visualization Symposium (PacificVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2002/1656/0/16560010",
"title": "Sound Glyphs Representing Inheritance Relationships",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2002/16560010/12OmNykTNmv",
"parentPublication": {
"id": "proceedings/iv/2002/1656/0",
"title": "Proceedings Sixth International Conference on Information Visualisation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2017/07/07445239",
"title": "A Systematic Review of Experimental Studies on Data Glyphs",
"doi": null,
"abstractUrl": "/journal/tg/2017/07/07445239/13rRUNvgz4m",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2014/12/06875973",
"title": "The Influence of Contour on Similarity Perception of Star Glyphs",
"doi": null,
"abstractUrl": "/journal/tg/2014/12/06875973/13rRUwhHcQV",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2018/7202/0/720200a071",
"title": "The Many-Faced Plot: Strategy for Automatic Glyph Generation",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2018/720200a071/17D45XDIXSv",
"parentPublication": {
"id": "proceedings/iv/2018/7202/0",
"title": "2018 22nd International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2018/7202/0/720200a058",
"title": "Visualizing Multidimensional Data in Treemaps with Adaptive Glyphs",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2018/720200a058/17D45XeKgvR",
"parentPublication": {
"id": "proceedings/iv/2018/7202/0",
"title": "2018 22nd International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2019/2838/0/283800a157",
"title": "Evaluation of Effectiveness of Glyphs to Enhance ChronoView",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2019/283800a157/1cMF9mvWMFO",
"parentPublication": {
"id": "proceedings/iv/2019/2838/0",
"title": "2019 23rd International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/09/09067088",
"title": "AgentVis: Visual Analysis of Agent Behavior With Hierarchical Glyphs",
"doi": null,
"abstractUrl": "/journal/tg/2021/09/09067088/1j1lyTz50k0",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2020/9134/0/913400a242",
"title": "A summarization glyph for sets of unreadable visual items in treemaps",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2020/913400a242/1rSRaQV3b3y",
"parentPublication": {
"id": "proceedings/iv/2020/9134/0",
"title": "2020 24th International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552906",
"articleId": "1xic46x3fmU",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552887",
"articleId": "1xibWySUs4U",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBaA5Jsces",
"name": "ttg202201-09557223s1-supp1-3114877.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09557223s1-supp1-3114877.mp4",
"extension": "mp4",
"size": "54.6 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xibWySUs4U",
"doi": "10.1109/TVCG.2021.3114803",
"abstract": "As uncertainty visualizations for general audiences become increasingly common, designers must understand the full impact of uncertainty communication techniques on viewers' decision processes. Prior work demonstrates mixed performance outcomes with respect to how individuals make decisions using various visual and textual depictions of uncertainty. Part of the inconsistency across findings may be due to an over-reliance on task accuracy, which cannot, on its own, provide a comprehensive understanding of how uncertainty visualization techniques support reasoning processes. In this work, we advance the debate surrounding the efficacy of modern 1D uncertainty visualizations by conducting converging quantitative and qualitative analyses of both the effort and strategies used by individuals when provided with quantile dotplots, density plots, interval plots, mean plots, and textual descriptions of uncertainty. We utilize two approaches for examining effort across uncertainty communication techniques: a measure of individual differences in working-memory capacity known as an operation span (OSPAN) task and self-reports of perceived workload via the NASA-TLX. The results reveal that both visualization methods and working-memory capacity impact participants' decisions. Specifically, quantile dotplots and density plots (i.e., distributional annotations) result in more accurate judgments than interval plots, textual descriptions of uncertainty, and mean plots (i.e., summary annotations). Additionally, participants' open-ended responses suggest that individuals viewing distributional annotations are more likely to employ a strategy that explicitly incorporates uncertainty into their judgments than those viewing summary annotations. When comparing quantile dotplots to density plots, this work finds that both methods are equally effective for low-working-memory individuals. However, for individuals with high-working-memory capacity, quantile dotplots evoke more accurate responses with less perceived effort. Given these results, we advocate for the inclusion of converging behavioral and subjective workload metrics in addition to accuracy performance to further disambiguate meaningful differences among visualization techniques.",
"abstracts": [
{
"abstractType": "Regular",
"content": "As uncertainty visualizations for general audiences become increasingly common, designers must understand the full impact of uncertainty communication techniques on viewers' decision processes. Prior work demonstrates mixed performance outcomes with respect to how individuals make decisions using various visual and textual depictions of uncertainty. Part of the inconsistency across findings may be due to an over-reliance on task accuracy, which cannot, on its own, provide a comprehensive understanding of how uncertainty visualization techniques support reasoning processes. In this work, we advance the debate surrounding the efficacy of modern 1D uncertainty visualizations by conducting converging quantitative and qualitative analyses of both the effort and strategies used by individuals when provided with quantile dotplots, density plots, interval plots, mean plots, and textual descriptions of uncertainty. We utilize two approaches for examining effort across uncertainty communication techniques: a measure of individual differences in working-memory capacity known as an operation span (OSPAN) task and self-reports of perceived workload via the NASA-TLX. The results reveal that both visualization methods and working-memory capacity impact participants' decisions. Specifically, quantile dotplots and density plots (i.e., distributional annotations) result in more accurate judgments than interval plots, textual descriptions of uncertainty, and mean plots (i.e., summary annotations). Additionally, participants' open-ended responses suggest that individuals viewing distributional annotations are more likely to employ a strategy that explicitly incorporates uncertainty into their judgments than those viewing summary annotations. When comparing quantile dotplots to density plots, this work finds that both methods are equally effective for low-working-memory individuals. However, for individuals with high-working-memory capacity, quantile dotplots evoke more accurate responses with less perceived effort. Given these results, we advocate for the inclusion of converging behavioral and subjective workload metrics in addition to accuracy performance to further disambiguate meaningful differences among visualization techniques.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "As uncertainty visualizations for general audiences become increasingly common, designers must understand the full impact of uncertainty communication techniques on viewers' decision processes. Prior work demonstrates mixed performance outcomes with respect to how individuals make decisions using various visual and textual depictions of uncertainty. Part of the inconsistency across findings may be due to an over-reliance on task accuracy, which cannot, on its own, provide a comprehensive understanding of how uncertainty visualization techniques support reasoning processes. In this work, we advance the debate surrounding the efficacy of modern 1D uncertainty visualizations by conducting converging quantitative and qualitative analyses of both the effort and strategies used by individuals when provided with quantile dotplots, density plots, interval plots, mean plots, and textual descriptions of uncertainty. We utilize two approaches for examining effort across uncertainty communication techniques: a measure of individual differences in working-memory capacity known as an operation span (OSPAN) task and self-reports of perceived workload via the NASA-TLX. The results reveal that both visualization methods and working-memory capacity impact participants' decisions. Specifically, quantile dotplots and density plots (i.e., distributional annotations) result in more accurate judgments than interval plots, textual descriptions of uncertainty, and mean plots (i.e., summary annotations). Additionally, participants' open-ended responses suggest that individuals viewing distributional annotations are more likely to employ a strategy that explicitly incorporates uncertainty into their judgments than those viewing summary annotations. When comparing quantile dotplots to density plots, this work finds that both methods are equally effective for low-working-memory individuals. However, for individuals with high-working-memory capacity, quantile dotplots evoke more accurate responses with less perceived effort. Given these results, we advocate for the inclusion of converging behavioral and subjective workload metrics in addition to accuracy performance to further disambiguate meaningful differences among visualization techniques.",
"title": "Examining Effort in 1D Uncertainty Communication Using Individual Differences in Working Memory and NASA-TLX",
"normalizedTitle": "Examining Effort in 1D Uncertainty Communication Using Individual Differences in Working Memory and NASA-TLX",
"fno": "09552887",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Uncertainty",
"Data Visualization",
"Visualization",
"Task Analysis",
"Annotations",
"Measurement Uncertainty",
"Cognition",
"Uncertainty Visualization",
"Working Memory",
"Individual Differences",
"Online OSPAN",
"Effort",
"Workload",
"NASA TLX"
],
"authors": [
{
"givenName": "Spencer C.",
"surname": "Castro",
"fullName": "Spencer C. Castro",
"affiliation": "University of California Merced in Management of Complex Systems, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "P. Samuel",
"surname": "Quinan",
"fullName": "P. Samuel Quinan",
"affiliation": "University of Utah School of Computing, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Helia",
"surname": "Hosseinpour",
"fullName": "Helia Hosseinpour",
"affiliation": "University of California Merced in Cognitive and Information Sciences, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Lace",
"surname": "Padilla",
"fullName": "Lace Padilla",
"affiliation": "University of California Merced in Cognitive and Information Sciences, United States",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "411-421",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "trans/tg/2016/01/07192667",
"title": "Visual Encodings of Temporal Uncertainty: A Comparative User Study",
"doi": null,
"abstractUrl": "/journal/tg/2016/01/07192667/13rRUwjGoLH",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2010/06/ttg2010060980",
"title": "Matching Visual Saliency to Confidence in Plots of Uncertain Data",
"doi": null,
"abstractUrl": "/journal/tg/2010/06/ttg2010060980/13rRUxZRbnY",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/01/08440816",
"title": "Hypothetical Outcome Plots Help Untrained Observers Judge Trends in Ambiguous Data",
"doi": null,
"abstractUrl": "/journal/tg/2019/01/08440816/17D45Xh13so",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09695348",
"title": "Visual Reasoning for Uncertainty in Spatio-temporal Events of Historical Figures",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09695348/1AvqJHyHeO4",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2021/2812/0/281200h396",
"title": "Scribble-Supervised Semantic Segmentation by Uncertainty Reduction on Neural Representation and Self-Supervision on Neural Eigenspace",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/281200h396/1BmLmd75nZS",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09904433",
"title": "Evaluating the Use of Uncertainty Visualisations for Imputations of Data Missing At Random in Scatterplots",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09904433/1H1gkkbe0hy",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/nicoint/2020/8771/0/09122371",
"title": "Visualization of Individual Variation of Multiple Annotators Working on Training Datasets for Machine Learning",
"doi": null,
"abstractUrl": "/proceedings-article/nicoint/2020/09122371/1kRSeLifK00",
"parentPublication": {
"id": "proceedings/nicoint/2020/8771/0",
"title": "2020 Nicograph International (NicoInt)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/02/09222364",
"title": "Visual Reasoning Strategies for Effect Size Judgments and Decisions",
"doi": null,
"abstractUrl": "/journal/tg/2021/02/09222364/1nTrxuPw4UM",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/01/09572234",
"title": "Professional Differences: A Comparative Study of Visualization Task Performance and Spatial Ability Across Disciplines",
"doi": null,
"abstractUrl": "/journal/tg/2022/01/09572234/1xH5FXdMnoA",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/acii/2021/0019/0/09597425",
"title": "Estimating continuous affect with label uncertainty",
"doi": null,
"abstractUrl": "/proceedings-article/acii/2021/09597425/1yylaKqSpH2",
"parentPublication": {
"id": "proceedings/acii/2021/0019/0",
"title": "2021 9th International Conference on Affective Computing and Intelligent Interaction (ACII)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09557223",
"articleId": "1xlvZajdjmo",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552179",
"articleId": "1xic7sgAtig",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zJiDrkhums",
"name": "ttg202201-09552887s1-supp1-3114803.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552887s1-supp1-3114803.pdf",
"extension": "pdf",
"size": "697 kB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xic7sgAtig",
"doi": "10.1109/TVCG.2021.3114761",
"abstract": "In this paper, we propose F2-Bubbles, a set overlay visualization technique that addresses overlapping artifacts and supports interactive editing with intelligent suggestions. The core of our method is a new, efficient set overlay construction algorithm that approximates the optimal set overlay by considering set elements and their non-set neighbors. Thanks to the efficiency of the algorithm, interactive editing is achieved, and with intelligent suggestions, users can easily and flexibly edit visualizations through direct manipulations with local adaptations. A quantitative comparison with state-of-the-art set visualization techniques and case studies demonstrate the effectiveness of our method and suggests that F2-Bubbles is a helpful technique for set visualization.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In this paper, we propose F2-Bubbles, a set overlay visualization technique that addresses overlapping artifacts and supports interactive editing with intelligent suggestions. The core of our method is a new, efficient set overlay construction algorithm that approximates the optimal set overlay by considering set elements and their non-set neighbors. Thanks to the efficiency of the algorithm, interactive editing is achieved, and with intelligent suggestions, users can easily and flexibly edit visualizations through direct manipulations with local adaptations. A quantitative comparison with state-of-the-art set visualization techniques and case studies demonstrate the effectiveness of our method and suggests that F2-Bubbles is a helpful technique for set visualization.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In this paper, we propose F2-Bubbles, a set overlay visualization technique that addresses overlapping artifacts and supports interactive editing with intelligent suggestions. The core of our method is a new, efficient set overlay construction algorithm that approximates the optimal set overlay by considering set elements and their non-set neighbors. Thanks to the efficiency of the algorithm, interactive editing is achieved, and with intelligent suggestions, users can easily and flexibly edit visualizations through direct manipulations with local adaptations. A quantitative comparison with state-of-the-art set visualization techniques and case studies demonstrate the effectiveness of our method and suggests that F2-Bubbles is a helpful technique for set visualization.",
"title": "F2-Bubbles: Faithful Bubble Set Construction and Flexible Editing",
"normalizedTitle": "F2-Bubbles: Faithful Bubble Set Construction and Flexible Editing",
"fno": "09552179",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Data Analysis",
"Data Visualisation",
"Peer To Peer Computing",
"Set Theory",
"Optimal Set Overlay",
"Set Elements",
"Nonset Neighbors",
"Interactive Editing",
"Intelligent Suggestions",
"Edit Visualizations",
"State Of The Art Set Visualization Techniques",
"F 2 Bubbles",
"Faithful Bubble Set Construction",
"Flexible Editing",
"Visualization Technique",
"Efficient Set",
"Construction Algorithm",
"Visualization",
"Data Visualization",
"Task Analysis",
"Clutter",
"Approximation Algorithms",
"Tuning",
"Micromechanical Devices",
"Set Visualization",
"Edge Crossing",
"Minimal Spanning Tree"
],
"authors": [
{
"givenName": "Yunhai",
"surname": "Wang",
"fullName": "Yunhai Wang",
"affiliation": "Shandong University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Da",
"surname": "Cheng",
"fullName": "Da Cheng",
"affiliation": "Shandong University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Zhirui",
"surname": "Wang",
"fullName": "Zhirui Wang",
"affiliation": "Shandong University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jian",
"surname": "Zhang",
"fullName": "Jian Zhang",
"affiliation": "CNIC, CAS, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Liang",
"surname": "Zhou",
"fullName": "Liang Zhou",
"affiliation": "National Institute of Health Data Science, Peking University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Gaoqi",
"surname": "He",
"fullName": "Gaoqi He",
"affiliation": "East China Normal University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Oliver",
"surname": "Deussen",
"fullName": "Oliver Deussen",
"affiliation": "Konstanz University, Germany",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "422-432",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/pg/2001/1227/0/12270169",
"title": "Stream Bubbles for Steady Flow Visualization",
"doi": null,
"abstractUrl": "/proceedings-article/pg/2001/12270169/12OmNBf94Yd",
"parentPublication": {
"id": "proceedings/pg/2001/1227/0",
"title": "Computer Graphics and Applications, Pacific Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2014/4103/0/4103a196",
"title": "Directional Aggregate Visualization of Large Scale Movement Data",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2014/4103a196/12OmNx8Ouzu",
"parentPublication": {
"id": "proceedings/iv/2014/4103/0",
"title": "2014 18th International Conference on Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pacificvis/2014/2874/0/2874a017",
"title": "Non-overlapping Aggregated Multivariate Glyphs for Moving Objects",
"doi": null,
"abstractUrl": "/proceedings-article/pacificvis/2014/2874a017/12OmNy2agTd",
"parentPublication": {
"id": "proceedings/pacificvis/2014/2874/0",
"title": "2014 IEEE Pacific Visualization Symposium (PacificVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2009/06/ttg2009061009",
"title": "Bubble Sets: Revealing Set Relations with Isocontours over Existing Visualizations",
"doi": null,
"abstractUrl": "/journal/tg/2009/06/ttg2009061009/13rRUwfZC0b",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/dsd/2018/7377/0/737700a163",
"title": "Visualization of Memory Map Information in Embedded System Design",
"doi": null,
"abstractUrl": "/proceedings-article/dsd/2018/737700a163/17D45VVho5j",
"parentPublication": {
"id": "proceedings/dsd/2018/7377/0",
"title": "2018 21st Euromicro Conference on Digital System Design (DSD)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/01/08445644",
"title": "Visualization of Bubble Formation in Porous Media",
"doi": null,
"abstractUrl": "/journal/tg/2019/01/08445644/17D45Wuc36G",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09721603",
"title": "Topological Simplifications of Hypergraphs",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09721603/1BhzoNy6wWA",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/dsc/2019/4528/0/452800a188",
"title": "Visualization of the Non-Dominated Solutions in Many-Objective Optimization",
"doi": null,
"abstractUrl": "/proceedings-article/dsc/2019/452800a188/1fHjOmQsZPi",
"parentPublication": {
"id": "proceedings/dsc/2019/4528/0",
"title": "2019 IEEE Fourth International Conference on Data Science in Cyberspace (DSC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2019/4803/0/480300j225",
"title": "Video Object Segmentation Using Space-Time Memory Networks",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2019/480300j225/1hVlL8ucCje",
"parentPublication": {
"id": "proceedings/iccv/2019/4803/0",
"title": "2019 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2020/9134/0/913400a467",
"title": "Spatiotemporal Phenomena Summarization through Static Visual Narratives",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2020/913400a467/1rSRaNwIpFK",
"parentPublication": {
"id": "proceedings/iv/2020/9134/0",
"title": "2020 24th International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552887",
"articleId": "1xibWySUs4U",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552459",
"articleId": "1xibZ9AqsLu",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBaXJySGME",
"name": "ttg202201-09552179s1-supp1-3114761.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552179s1-supp1-3114761.pdf",
"extension": "pdf",
"size": "9.36 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xibZ9AqsLu",
"doi": "10.1109/TVCG.2021.3114834",
"abstract": "Creating comprehensible visualizations of highly overlapping set-typed data is a challenging task due to its complexity. To facilitate insights into set connectivity and to leverage semantic relations between intersections, we propose a fast two-step layout technique for Euler diagrams that are both well-matched and well-formed. Our method conforms to established form guidelines for Euler diagrams regarding semantics, aesthetics, and readability. First, we establish an initial ordering of the data, which we then use to incrementally create a planar, connected, and monotone dual graph representation. In the next step, the graph is transformed into a circular layout that maintains the semantics and yields simple Euler diagrams with smooth curves. When the data cannot be represented by simple diagrams, our algorithm always falls back to a solution that is not well-formed but still well-matched, whereas previous methods often fail to produce expected results. We show the usefulness of our method for visualizing set-typed data using examples from text analysis and infographics. Furthermore, we discuss the characteristics of our approach and evaluate our method against state-of-the-art methods.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Creating comprehensible visualizations of highly overlapping set-typed data is a challenging task due to its complexity. To facilitate insights into set connectivity and to leverage semantic relations between intersections, we propose a fast two-step layout technique for Euler diagrams that are both well-matched and well-formed. Our method conforms to established form guidelines for Euler diagrams regarding semantics, aesthetics, and readability. First, we establish an initial ordering of the data, which we then use to incrementally create a planar, connected, and monotone dual graph representation. In the next step, the graph is transformed into a circular layout that maintains the semantics and yields simple Euler diagrams with smooth curves. When the data cannot be represented by simple diagrams, our algorithm always falls back to a solution that is not well-formed but still well-matched, whereas previous methods often fail to produce expected results. We show the usefulness of our method for visualizing set-typed data using examples from text analysis and infographics. Furthermore, we discuss the characteristics of our approach and evaluate our method against state-of-the-art methods.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Creating comprehensible visualizations of highly overlapping set-typed data is a challenging task due to its complexity. To facilitate insights into set connectivity and to leverage semantic relations between intersections, we propose a fast two-step layout technique for Euler diagrams that are both well-matched and well-formed. Our method conforms to established form guidelines for Euler diagrams regarding semantics, aesthetics, and readability. First, we establish an initial ordering of the data, which we then use to incrementally create a planar, connected, and monotone dual graph representation. In the next step, the graph is transformed into a circular layout that maintains the semantics and yields simple Euler diagrams with smooth curves. When the data cannot be represented by simple diagrams, our algorithm always falls back to a solution that is not well-formed but still well-matched, whereas previous methods often fail to produce expected results. We show the usefulness of our method for visualizing set-typed data using examples from text analysis and infographics. Furthermore, we discuss the characteristics of our approach and evaluate our method against state-of-the-art methods.",
"title": "<sc>SP</sc>E<sc>ULER</sc>: Semantics-preserving Euler Diagrams",
"normalizedTitle": "SPEULER: Semantics-preserving Euler Diagrams",
"fno": "09552459",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Data Visualisation",
"Graph Theory",
"Text Analysis",
"Circular Layout",
"Yields Simple Euler Diagrams",
"Simple Diagrams",
"Semantics Preserving Euler Diagrams",
"Comprehensible Visualizations",
"Set Connectivity",
"Leverage Semantic Relations",
"Two Step Layout Technique",
"Established Form Guidelines",
"Monotone Dual Graph Representation",
"Data Visualization",
"Task Analysis",
"Faces",
"Semantics",
"Layout",
"Guidelines",
"Visualization",
"Euler Diagrams",
"Venn Diagrams",
"Set Visualization",
"Layout Algorithm"
],
"authors": [
{
"givenName": "Rebecca",
"surname": "Kehlbeck",
"fullName": "Rebecca Kehlbeck",
"affiliation": "University of Konstanz, Germany",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jochen",
"surname": "Görtler",
"fullName": "Jochen Görtler",
"affiliation": "University of Konstanz, Germany",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yunhai",
"surname": "Wang",
"fullName": "Yunhai Wang",
"affiliation": "Shandong University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Oliver",
"surname": "Deussen",
"fullName": "Oliver Deussen",
"affiliation": "University of Konstanz, Germany",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "433-442",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/iv/2008/3268/0/3268a594",
"title": "Visualise Undrawable Euler Diagrams",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2008/3268a594/12OmNBOllkb",
"parentPublication": {
"id": "proceedings/iv/2008/3268/0",
"title": "2008 12th International Conference Information Visualisation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vlhcc/2014/4035/0/06883063",
"title": "Properties of euler diagrams and graphs in combination",
"doi": null,
"abstractUrl": "/proceedings-article/vlhcc/2014/06883063/12OmNvA1hE8",
"parentPublication": {
"id": "proceedings/vlhcc/2014/4035/0",
"title": "2014 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2003/1988/0/19880272",
"title": "Layout Metrics for Euler Diagrams",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2003/19880272/12OmNvD8RBs",
"parentPublication": {
"id": "proceedings/iv/2003/1988/0",
"title": "Proceedings on Seventh International Conference on Information Visualization, 2003. IV 2003.",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vlhcc/2011/1246/0/06070401",
"title": "Drawing Euler diagrams with circles and ellipses",
"doi": null,
"abstractUrl": "/proceedings-article/vlhcc/2011/06070401/12OmNvpew49",
"parentPublication": {
"id": "proceedings/vlhcc/2011/1246/0",
"title": "2011 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC 2011)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vlhcc/2011/1246/0/06070382",
"title": "SketchSet: Creating Euler diagrams using pen or mouse",
"doi": null,
"abstractUrl": "/proceedings-article/vlhcc/2011/06070382/12OmNx965CA",
"parentPublication": {
"id": "proceedings/vlhcc/2011/1246/0",
"title": "2011 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC 2011)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2007/2900/0/29000771",
"title": "Evaluating the Comprehension of Euler Diagrams",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2007/29000771/12OmNxjjEhx",
"parentPublication": {
"id": "proceedings/iv/2007/2900/0",
"title": "2007 11th International Conference Information Visualization (IV '07)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vlhcc/2013/0369/0/06645262",
"title": "Improving user comprehension of Euler diagrams",
"doi": null,
"abstractUrl": "/proceedings-article/vlhcc/2013/06645262/12OmNxveNOL",
"parentPublication": {
"id": "proceedings/vlhcc/2013/0369/0",
"title": "2013 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2008/3268/0/3268a585",
"title": "Embedding Wellformed Euler Diagrams",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2008/3268a585/12OmNyuya3M",
"parentPublication": {
"id": "proceedings/iv/2008/3268/0",
"title": "2008 12th International Conference Information Visualisation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icgciot/2015/7910/0/07380712",
"title": "Spherule diagrams: A matrix-based set visualization compared with Euler diagrams",
"doi": null,
"abstractUrl": "/proceedings-article/icgciot/2015/07380712/12OmNyvGyfY",
"parentPublication": {
"id": "proceedings/icgciot/2015/7910/0",
"title": "2015 International Conference on Green Computing and Internet of Things (ICGCIoT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2011/01/ttg2011010088",
"title": "Inductively Generating Euler Diagrams",
"doi": null,
"abstractUrl": "/journal/tg/2011/01/ttg2011010088/13rRUNvgziB",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552179",
"articleId": "1xic7sgAtig",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552465",
"articleId": "1xic9toQQrC",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBaybOg2WI",
"name": "ttg202201-09552459s1-supp1-3114834.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552459s1-supp1-3114834.pdf",
"extension": "pdf",
"size": "452 kB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xic9toQQrC",
"doi": "10.1109/TVCG.2021.3114679",
"abstract": "Probabilistic graphs are challenging to visualize using the traditional node-link diagram. Encoding edge probability using visual variables like width or fuzziness makes it difficult for users of static network visualizations to estimate network statistics like densities, isolates, path lengths, or clustering under uncertainty. We introduce Network Hypothetical Outcome Plots (NetHOPs), a visualization technique that animates a sequence of network realizations sampled from a network distribution defined by probabilistic edges. NetHOPs employ an aggregation and anchoring algorithm used in dynamic and longitudinal graph drawing to parameterize layout stability for uncertainty estimation. We present a community matching algorithm to enable visualizing the uncertainty of cluster membership and community occurrence. We describe the results of a study in which 51 network experts used NetHOPs to complete a set of common visual analysis tasks and reported how they perceived network structures and properties subject to uncertainty. Participants' estimates fell, on average, within 11% of the ground truth statistics, suggesting NetHOPs can be a reasonable approach for enabling network analysts to reason about multiple properties under uncertainty. Participants appeared to articulate the distribution of network statistics slightly more accurately when they could manipulate the layout anchoring and the animation speed. Based on these findings, we synthesize design recommendations for developing and using animated visualizations for probabilistic networks.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Probabilistic graphs are challenging to visualize using the traditional node-link diagram. Encoding edge probability using visual variables like width or fuzziness makes it difficult for users of static network visualizations to estimate network statistics like densities, isolates, path lengths, or clustering under uncertainty. We introduce Network Hypothetical Outcome Plots (NetHOPs), a visualization technique that animates a sequence of network realizations sampled from a network distribution defined by probabilistic edges. NetHOPs employ an aggregation and anchoring algorithm used in dynamic and longitudinal graph drawing to parameterize layout stability for uncertainty estimation. We present a community matching algorithm to enable visualizing the uncertainty of cluster membership and community occurrence. We describe the results of a study in which 51 network experts used NetHOPs to complete a set of common visual analysis tasks and reported how they perceived network structures and properties subject to uncertainty. Participants' estimates fell, on average, within 11% of the ground truth statistics, suggesting NetHOPs can be a reasonable approach for enabling network analysts to reason about multiple properties under uncertainty. Participants appeared to articulate the distribution of network statistics slightly more accurately when they could manipulate the layout anchoring and the animation speed. Based on these findings, we synthesize design recommendations for developing and using animated visualizations for probabilistic networks.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Probabilistic graphs are challenging to visualize using the traditional node-link diagram. Encoding edge probability using visual variables like width or fuzziness makes it difficult for users of static network visualizations to estimate network statistics like densities, isolates, path lengths, or clustering under uncertainty. We introduce Network Hypothetical Outcome Plots (NetHOPs), a visualization technique that animates a sequence of network realizations sampled from a network distribution defined by probabilistic edges. NetHOPs employ an aggregation and anchoring algorithm used in dynamic and longitudinal graph drawing to parameterize layout stability for uncertainty estimation. We present a community matching algorithm to enable visualizing the uncertainty of cluster membership and community occurrence. We describe the results of a study in which 51 network experts used NetHOPs to complete a set of common visual analysis tasks and reported how they perceived network structures and properties subject to uncertainty. Participants' estimates fell, on average, within 11% of the ground truth statistics, suggesting NetHOPs can be a reasonable approach for enabling network analysts to reason about multiple properties under uncertainty. Participants appeared to articulate the distribution of network statistics slightly more accurately when they could manipulate the layout anchoring and the animation speed. Based on these findings, we synthesize design recommendations for developing and using animated visualizations for probabilistic networks.",
"title": "Visualizing Uncertainty in Probabilistic Graphs with Network Hypothetical Outcome Plots (NetHOPs)",
"normalizedTitle": "Visualizing Uncertainty in Probabilistic Graphs with Network Hypothetical Outcome Plots (NetHOPs)",
"fno": "09552465",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Computer Animation",
"Data Visualisation",
"Graph Theory",
"Image Representation",
"Probability",
"Probabilistic Graphs",
"Network Hypothetical Outcome Plots",
"Net HO Ps",
"Traditional Node Link Diagram",
"Encoding Edge Probability",
"Visual Variables",
"Static Network Visualizations",
"Network Statistics",
"Visualization Technique",
"Network Realizations",
"Network Distribution",
"Probabilistic Edges",
"Aggregation",
"Anchoring Algorithm",
"Dynamic Graph",
"Longitudinal Graph",
"Uncertainty Estimation",
"51 Network Experts",
"Common Visual Analysis Tasks",
"Network Structures",
"Network Analysts",
"Animated Visualizations",
"Probabilistic Networks",
"Probabilistic Logic",
"Visualization",
"Uncertainty",
"Layout",
"Task Analysis",
"Stability Analysis",
"Encoding",
"Network",
"Uncertainty",
"Application"
],
"authors": [
{
"givenName": "Dongping",
"surname": "Zhang",
"fullName": "Dongping Zhang",
"affiliation": "Northwestern University, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Eytan",
"surname": "Adar",
"fullName": "Eytan Adar",
"affiliation": "University of Michigan, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jessica",
"surname": "Hullman",
"fullName": "Jessica Hullman",
"affiliation": "Northwestern University, United States",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "443-453",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/aina/2012/4651/0/06184913",
"title": "Uncertainty in Probabilistic Trust Models",
"doi": null,
"abstractUrl": "/proceedings-article/aina/2012/06184913/12OmNAYoKwg",
"parentPublication": {
"id": "proceedings/aina/2012/4651/0",
"title": "2012 IEEE 26th International Conference on Advanced Information Networking and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ieee-infovis/2002/1751/0/17510037",
"title": "Visualizing Data with Bounded Uncertainty",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-infovis/2002/17510037/12OmNrFkeWk",
"parentPublication": {
"id": "proceedings/ieee-infovis/2002/1751/0",
"title": "Information Visualization, IEEE Symposium on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ifita/2009/3600/1/3600a182",
"title": "Supporting Uncertainty in Indexing and Querying of Moving Objects in Networks Databases",
"doi": null,
"abstractUrl": "/proceedings-article/ifita/2009/3600a182/12OmNyQ7FFE",
"parentPublication": {
"id": "proceedings/ifita/2009/3600/3",
"title": "Information Technology and Applications, International Forum on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2012/12/ttg2012122526",
"title": "Visualizing Flow of Uncertainty through Analytical Processes",
"doi": null,
"abstractUrl": "/journal/tg/2012/12/ttg2012122526/13rRUyY28Yv",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/big-data/2017/2715/0/08257906",
"title": "Collective subjective logic: Scalable uncertainty-based opinion inference",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2017/08257906/17D45Vu1Tya",
"parentPublication": {
"id": "proceedings/big-data/2017/2715/0",
"title": "2017 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/01/08440816",
"title": "Hypothetical Outcome Plots Help Untrained Observers Judge Trends in Ambiguous Data",
"doi": null,
"abstractUrl": "/journal/tg/2019/01/08440816/17D45Xh13so",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/ts/5555/01/10057480",
"title": "Modelling Second-Order Uncertainty in State Machines",
"doi": null,
"abstractUrl": "/journal/ts/5555/01/10057480/1LbFrPLyW1q",
"parentPublication": {
"id": "trans/ts",
"title": "IEEE Transactions on Software Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pacificvis/2019/9226/0/922600a227",
"title": "Uncertainty-Aware Ramachandran Plots",
"doi": null,
"abstractUrl": "/proceedings-article/pacificvis/2019/922600a227/1dlwrfwAikw",
"parentPublication": {
"id": "proceedings/pacificvis/2019/9226/0",
"title": "2019 IEEE Pacific Visualization Symposium (PacificVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2020/7168/0/716800m2011",
"title": "Uncertainty-Aware CNNs for Depth Completion: Uncertainty from Beginning to End",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2020/716800m2011/1m3nqBO2klG",
"parentPublication": {
"id": "proceedings/cvpr/2020/7168/0",
"title": "2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2021/4509/0/450900n3891",
"title": "Learning Probabilistic Ordinal Embeddings for Uncertainty-Aware Regression",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2021/450900n3891/1yeItyLY6o8",
"parentPublication": {
"id": "proceedings/cvpr/2021/4509/0",
"title": "2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552459",
"articleId": "1xibZ9AqsLu",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09548797",
"articleId": "1xeSlZqOf8A",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBb4BgEdtC",
"name": "ttg202201-09552465s1-tvcg-3114679-mm.zip",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552465s1-tvcg-3114679-mm.zip",
"extension": "zip",
"size": "200 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xeSlZqOf8A",
"doi": "10.1109/TVCG.2021.3114692",
"abstract": "For many households, investing for retirement is one of the most significant decisions and is fraught with uncertainty. In a classic study in behavioral economics, Benartzi and Thaler (1999) found evidence using bar charts that investors exhibit myopic loss aversion in retirement decisions: Investors overly focus on the potential for short-term losses, leading them to invest less in riskier assets and miss out on higher long-term returns. Recently, advances in uncertainty visualizations have shown improvements in decision-making under uncertainty in a variety of tasks. In this paper, we conduct a controlled and incentivized crowdsourced experiment replicating Benartzi and Thaler (1999) and extending it to measure the effect of different uncertainty representations on myopic loss aversion. Consistent with the original study, we find evidence of myopic loss aversion with bar charts and find that participants make better investment decisions with longer evaluation periods. We also find that common uncertainty representations such as interval plots and bar charts achieve the highest mean expected returns while other uncertainty visualizations lead to poorer long-term performance and strong effects on the equity premium. Qualitative feedback further suggests that different uncertainty representations lead to visual reasoning heuristics that can either mitigate or encourage a focus on potential short-term losses. We discuss implications of our results on using uncertainty visualizations for retirement decisions in practice and possible extensions for future work.",
"abstracts": [
{
"abstractType": "Regular",
"content": "For many households, investing for retirement is one of the most significant decisions and is fraught with uncertainty. In a classic study in behavioral economics, Benartzi and Thaler (1999) found evidence using bar charts that investors exhibit myopic loss aversion in retirement decisions: Investors overly focus on the potential for short-term losses, leading them to invest less in riskier assets and miss out on higher long-term returns. Recently, advances in uncertainty visualizations have shown improvements in decision-making under uncertainty in a variety of tasks. In this paper, we conduct a controlled and incentivized crowdsourced experiment replicating Benartzi and Thaler (1999) and extending it to measure the effect of different uncertainty representations on myopic loss aversion. Consistent with the original study, we find evidence of myopic loss aversion with bar charts and find that participants make better investment decisions with longer evaluation periods. We also find that common uncertainty representations such as interval plots and bar charts achieve the highest mean expected returns while other uncertainty visualizations lead to poorer long-term performance and strong effects on the equity premium. Qualitative feedback further suggests that different uncertainty representations lead to visual reasoning heuristics that can either mitigate or encourage a focus on potential short-term losses. We discuss implications of our results on using uncertainty visualizations for retirement decisions in practice and possible extensions for future work.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "For many households, investing for retirement is one of the most significant decisions and is fraught with uncertainty. In a classic study in behavioral economics, Benartzi and Thaler (1999) found evidence using bar charts that investors exhibit myopic loss aversion in retirement decisions: Investors overly focus on the potential for short-term losses, leading them to invest less in riskier assets and miss out on higher long-term returns. Recently, advances in uncertainty visualizations have shown improvements in decision-making under uncertainty in a variety of tasks. In this paper, we conduct a controlled and incentivized crowdsourced experiment replicating Benartzi and Thaler (1999) and extending it to measure the effect of different uncertainty representations on myopic loss aversion. Consistent with the original study, we find evidence of myopic loss aversion with bar charts and find that participants make better investment decisions with longer evaluation periods. We also find that common uncertainty representations such as interval plots and bar charts achieve the highest mean expected returns while other uncertainty visualizations lead to poorer long-term performance and strong effects on the equity premium. Qualitative feedback further suggests that different uncertainty representations lead to visual reasoning heuristics that can either mitigate or encourage a focus on potential short-term losses. We discuss implications of our results on using uncertainty visualizations for retirement decisions in practice and possible extensions for future work.",
"title": "Effect of uncertainty visualizations on myopic loss aversion and the equity premium puzzle in retirement investment decisions",
"normalizedTitle": "Effect of uncertainty visualizations on myopic loss aversion and the equity premium puzzle in retirement investment decisions",
"fno": "09548797",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Data Visualisation",
"Decision Making",
"Economics",
"Investment",
"Risk Analysis",
"Stock Markets",
"Uncertainty Visualizations",
"Myopic Loss Aversion",
"Retirement Investment Decisions",
"Significant Decisions",
"Thaler",
"Bar Charts",
"Retirement Decisions",
"Short Term Losses",
"Long Term Returns",
"Decision Making",
"Different Uncertainty Representations",
"Common Uncertainty Representations",
"Uncertainty",
"Retirement",
"Visualization",
"Investment",
"Resource Management",
"Economics",
"Bars",
"Uncertainty Visualizations",
"Myopic Loss Aversion",
"Retirement Investing",
"Equity Premium Puzzle"
],
"authors": [
{
"givenName": "Ryan",
"surname": "Wesslen",
"fullName": "Ryan Wesslen",
"affiliation": "UNC-Charlotte, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Alireza",
"surname": "Karduni",
"fullName": "Alireza Karduni",
"affiliation": "UNC-Charlotte, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Douglas",
"surname": "Markant",
"fullName": "Douglas Markant",
"affiliation": "UNC-Charlotte, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Wenwen",
"surname": "Dou",
"fullName": "Wenwen Dou",
"affiliation": "UNC-Charlotte, United States",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "454-464",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/cso/2014/5372/0/5372a074",
"title": "Incentive Mechanism for University Teachers under Multi-task Principal-Agent Model",
"doi": null,
"abstractUrl": "/proceedings-article/cso/2014/5372a074/12OmNAObbGy",
"parentPublication": {
"id": "proceedings/cso/2014/5372/0",
"title": "2014 Seventh International Joint Conference on Computational Sciences and Optimization (CSO)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hicss/2013/4892/0/4892e166",
"title": "Technology Investment Decision-Making under Uncertainty: The Case of Mobile Payment Systems",
"doi": null,
"abstractUrl": "/proceedings-article/hicss/2013/4892e166/12OmNBNM8O6",
"parentPublication": {
"id": "proceedings/hicss/2013/4892/0",
"title": "2013 46th Hawaii International Conference on System Sciences",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccis/2013/5004/0/5004a633",
"title": "Economic Evaluation of EOR Project Based on Options Differential Equation Method",
"doi": null,
"abstractUrl": "/proceedings-article/iccis/2013/5004a633/12OmNrHSD6e",
"parentPublication": {
"id": "proceedings/iccis/2013/5004/0",
"title": "2013 International Conference on Computational and Information Sciences",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bigdataservice/2015/8128/0/8128a341",
"title": "Inferring Risk Aversion for Decentralized Investment Portfolios",
"doi": null,
"abstractUrl": "/proceedings-article/bigdataservice/2015/8128a341/12OmNvSbByl",
"parentPublication": {
"id": "proceedings/bigdataservice/2015/8128/0",
"title": "2015 IEEE First International Conference on Big Data Computing Service and Applications (BigDataService)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hicss/2015/7367/0/7367b240",
"title": "Multi-criteria Decision Support for Investment Decisions: Examining the Interactive Effects of Risk Profile, Information Horizon, and Prospect Format",
"doi": null,
"abstractUrl": "/proceedings-article/hicss/2015/7367b240/12OmNyuPLbD",
"parentPublication": {
"id": "proceedings/hicss/2015/7367/0",
"title": "2015 48th Hawaii International Conference on System Sciences (HICSS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bife/2012/4750/0/4750a274",
"title": "A jump-diffusion approach to modelling software security investment",
"doi": null,
"abstractUrl": "/proceedings-article/bife/2012/4750a274/12OmNz2TCDN",
"parentPublication": {
"id": "proceedings/bife/2012/4750/0",
"title": "2012 Fifth International Conference on Business Intelligence and Financial Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2015/09/07056447",
"title": "Non-Myopic Adaptive Route Planning in Uncertain Congestion Environments",
"doi": null,
"abstractUrl": "/journal/tk/2015/09/07056447/13rRUxASuGK",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/sp/2010/01/msp2010010053",
"title": "The Iterated Weakest Link",
"doi": null,
"abstractUrl": "/magazine/sp/2010/01/msp2010010053/13rRUxNEqU3",
"parentPublication": {
"id": "mags/sp",
"title": "IEEE Security & Privacy",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hicss/2007/2755/0/04076421",
"title": "Advice Availability and Gender Differences in Risky Decision Making: A Study of Online Retirement Planning",
"doi": null,
"abstractUrl": "/proceedings-article/hicss/2007/04076421/17D45XacGjM",
"parentPublication": {
"id": "proceedings/hicss/2007/2755/0",
"title": "2007 40th Annual Hawaii International Conference on System Sciences (HICSS'07)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/01/09552205",
"title": "Visualization Equilibrium",
"doi": null,
"abstractUrl": "/journal/tg/2022/01/09552205/1xic4zmtlra",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552465",
"articleId": "1xic9toQQrC",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552205",
"articleId": "1xic4zmtlra",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zHDGBp9S6c",
"name": "ttg202201-09548797s1-tvcg-3114692-mm.zip",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09548797s1-tvcg-3114692-mm.zip",
"extension": "zip",
"size": "129 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xic4zmtlra",
"doi": "10.1109/TVCG.2021.3114842",
"abstract": "In many real-world strategic settings, people use information displays to make decisions. In these settings, an information provider chooses which information to provide to strategic agents and how to present it, and agents formulate a best response based on the information and their anticipation of how others will behave. We contribute the results of a controlled online experiment to examine how the provision and presentation of information impacts people's decisions in a congestion game. Our experiment compares how different visualization approaches for displaying this information, including bar charts and hypothetical outcome plots, and different information conditions, including where the visualized information is private versus public (i.e., available to all agents), affect decision making and welfare. We characterize the effects of visualization anticipation, referring to changes to behavior when an agent goes from alone having access to a visualization to knowing that others also have access to the visualization to guide their decisions. We also empirically identify the visualization equilibrium, i.e., the visualization for which the visualized outcome of agents' decisions matches the realized decisions of the agents who view it. We reflect on the implications of visualization equilibria and visualization anticipation for designing information displays for real-world strategic settings.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In many real-world strategic settings, people use information displays to make decisions. In these settings, an information provider chooses which information to provide to strategic agents and how to present it, and agents formulate a best response based on the information and their anticipation of how others will behave. We contribute the results of a controlled online experiment to examine how the provision and presentation of information impacts people's decisions in a congestion game. Our experiment compares how different visualization approaches for displaying this information, including bar charts and hypothetical outcome plots, and different information conditions, including where the visualized information is private versus public (i.e., available to all agents), affect decision making and welfare. We characterize the effects of visualization anticipation, referring to changes to behavior when an agent goes from alone having access to a visualization to knowing that others also have access to the visualization to guide their decisions. We also empirically identify the visualization equilibrium, i.e., the visualization for which the visualized outcome of agents' decisions matches the realized decisions of the agents who view it. We reflect on the implications of visualization equilibria and visualization anticipation for designing information displays for real-world strategic settings.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In many real-world strategic settings, people use information displays to make decisions. In these settings, an information provider chooses which information to provide to strategic agents and how to present it, and agents formulate a best response based on the information and their anticipation of how others will behave. We contribute the results of a controlled online experiment to examine how the provision and presentation of information impacts people's decisions in a congestion game. Our experiment compares how different visualization approaches for displaying this information, including bar charts and hypothetical outcome plots, and different information conditions, including where the visualized information is private versus public (i.e., available to all agents), affect decision making and welfare. We characterize the effects of visualization anticipation, referring to changes to behavior when an agent goes from alone having access to a visualization to knowing that others also have access to the visualization to guide their decisions. We also empirically identify the visualization equilibrium, i.e., the visualization for which the visualized outcome of agents' decisions matches the realized decisions of the agents who view it. We reflect on the implications of visualization equilibria and visualization anticipation for designing information displays for real-world strategic settings.",
"title": "Visualization Equilibrium",
"normalizedTitle": "Visualization Equilibrium",
"fno": "09552205",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Data Visualisation",
"Decision Making",
"Game Theory",
"Internet",
"Different Visualization Approaches",
"Hypothetical Outcome Plots",
"Different Information Conditions",
"Visualized Information",
"Decision Making",
"Welfare",
"Visualization Anticipation",
"Visualization Equilibrium",
"Visualized Outcome",
"Realized Decisions",
"Visualization Equilibria",
"Information Displays",
"Real World Strategic Settings",
"Information Provider",
"Strategic Agents",
"Controlled Online Experiment",
"Data Visualization",
"Uncertainty",
"Games",
"Visualization",
"Nash Equilibrium",
"Bars",
"Economics",
"Visualization Equilibrium",
"Uncertainty Visualization",
"Strategic Communication",
"Nash Equilibrium"
],
"authors": [
{
"givenName": "Paula",
"surname": "Kayongo",
"fullName": "Paula Kayongo",
"affiliation": "Northwestern University, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Glenn",
"surname": "Sun",
"fullName": "Glenn Sun",
"affiliation": "University of California, Los Angeles, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jason",
"surname": "Hartline",
"fullName": "Jason Hartline",
"affiliation": "Northwestern University, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jessica",
"surname": "Hullman",
"fullName": "Jessica Hullman",
"affiliation": "Northwestern University, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "465-474",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/cinc/2009/3645/2/3645b355",
"title": "Approximate Computation of Nash Equilibrium in Complex Simulated Economic System",
"doi": null,
"abstractUrl": "/proceedings-article/cinc/2009/3645b355/12OmNB8kHTK",
"parentPublication": {
"id": "cinc/2009/3645/2",
"title": "Computational Intelligence and Natural Computing, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/apscc/2008/3473/0/3473a795",
"title": "Nash Equilibrium: Better Strategy for Agents Coordination",
"doi": null,
"abstractUrl": "/proceedings-article/apscc/2008/3473a795/12OmNCdTeON",
"parentPublication": {
"id": "proceedings/apscc/2008/3473/0",
"title": "2008 IEEE Asia-Pacific Services Computing Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/waina/2009/3639/0/3639a001",
"title": "Fuzzy Communication Leading to Equilibrium through Possibility Messages",
"doi": null,
"abstractUrl": "/proceedings-article/waina/2009/3639a001/12OmNvIfDR8",
"parentPublication": {
"id": "proceedings/waina/2009/3639/0",
"title": "2009 International Conference on Advanced Information Networking and Applications Workshops",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/esiat/2009/3682/3/3682c598",
"title": "An Analysis of Manufacturers' R&D Decision-Making in Defense Procurement with Incomplete Information",
"doi": null,
"abstractUrl": "/proceedings-article/esiat/2009/3682c598/12OmNx5piZc",
"parentPublication": {
"id": "proceedings/esiat/2009/3682/3",
"title": "Environmental Science and Information Application Technology, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ictai/2012/0227/1/06495062",
"title": "Incorporating Fairness into Infinitely Repeated Games with Conflicting Interests for Conflicts Elimination",
"doi": null,
"abstractUrl": "/proceedings-article/ictai/2012/06495062/12OmNx5pj2V",
"parentPublication": {
"id": "proceedings/ictai/2012/0227/1",
"title": "2012 IEEE 24th International Conference on Tools with Artificial Intelligence (ICTAI 2012)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ictai/2017/3876/0/387601a404",
"title": "Midgame Solving: A New Weapon for Efficient Large-Scale Equilibrium Approximation",
"doi": null,
"abstractUrl": "/proceedings-article/ictai/2017/387601a404/12OmNxvO05p",
"parentPublication": {
"id": "proceedings/ictai/2017/3876/0",
"title": "2017 IEEE 29th International Conference on Tools with Artificial Intelligence (ICTAI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/dcc/2011/279/0/05749489",
"title": "Conflict in Distributed Hypothesis Testing with Quantized Prior Probabilities",
"doi": null,
"abstractUrl": "/proceedings-article/dcc/2011/05749489/12OmNzwpU6m",
"parentPublication": {
"id": "proceedings/dcc/2011/279/0",
"title": "2011 Data Compression Conference (DCC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/ex/2017/01/mex2017010017",
"title": "Cooperation and Competition When Bidding for Complex Projects: Centralized and Decentralized Perspectives",
"doi": null,
"abstractUrl": "/magazine/ex/2017/01/mex2017010017/13rRUwh80yN",
"parentPublication": {
"id": "mags/ex",
"title": "IEEE Intelligent Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2017/01/07539634",
"title": "VLAT: Development of a Visualization Literacy Assessment Test",
"doi": null,
"abstractUrl": "/journal/tg/2017/01/07539634/13rRUxASuhE",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09904456",
"title": "Measuring Effects of Spatial Visualization and Domain on Visualization Task Performance: A Comparative Study",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09904456/1H1gmktPnLa",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09548797",
"articleId": "1xeSlZqOf8A",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552870",
"articleId": "1xic90zZWDu",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBaOKelAuQ",
"name": "ttg202201-09552205s1-tvcg-3114842-mm.zip",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552205s1-tvcg-3114842-mm.zip",
"extension": "zip",
"size": "5.81 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xic90zZWDu",
"doi": "10.1109/TVCG.2021.3114790",
"abstract": "How to achieve academic career success has been a long-standing research question in social science research. With the growing availability of large-scale well-documented academic profiles and career trajectories, scholarly interest in career success has been reinvigorated, which has emerged to be an active research domain called the Science of Science (i.e., SciSci). In this study, we adopt an innovative dynamic perspective to examine how individual and social factors will influence career success over time. We propose <italic>ACSeeker</italic>, an interactive visual analytics approach to explore the potential factors of success and how the influence of multiple factors changes at different stages of academic careers. We first applied a Multi-factor Impact Analysis framework to estimate the effect of different factors on academic career success over time. We then developed a visual analytics system to understand the dynamic effects interactively. A novel timeline is designed to reveal and compare the factor impacts based on the whole population. A customized career line showing the individual career development is provided to allow a detailed inspection. To validate the effectiveness and usability of <italic>ACSeeker</italic>, we report two case studies and interviews with a social scientist and general researchers.",
"abstracts": [
{
"abstractType": "Regular",
"content": "How to achieve academic career success has been a long-standing research question in social science research. With the growing availability of large-scale well-documented academic profiles and career trajectories, scholarly interest in career success has been reinvigorated, which has emerged to be an active research domain called the Science of Science (i.e., SciSci). In this study, we adopt an innovative dynamic perspective to examine how individual and social factors will influence career success over time. We propose <italic>ACSeeker</italic>, an interactive visual analytics approach to explore the potential factors of success and how the influence of multiple factors changes at different stages of academic careers. We first applied a Multi-factor Impact Analysis framework to estimate the effect of different factors on academic career success over time. We then developed a visual analytics system to understand the dynamic effects interactively. A novel timeline is designed to reveal and compare the factor impacts based on the whole population. A customized career line showing the individual career development is provided to allow a detailed inspection. To validate the effectiveness and usability of <italic>ACSeeker</italic>, we report two case studies and interviews with a social scientist and general researchers.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "How to achieve academic career success has been a long-standing research question in social science research. With the growing availability of large-scale well-documented academic profiles and career trajectories, scholarly interest in career success has been reinvigorated, which has emerged to be an active research domain called the Science of Science (i.e., SciSci). In this study, we adopt an innovative dynamic perspective to examine how individual and social factors will influence career success over time. We propose ACSeeker, an interactive visual analytics approach to explore the potential factors of success and how the influence of multiple factors changes at different stages of academic careers. We first applied a Multi-factor Impact Analysis framework to estimate the effect of different factors on academic career success over time. We then developed a visual analytics system to understand the dynamic effects interactively. A novel timeline is designed to reveal and compare the factor impacts based on the whole population. A customized career line showing the individual career development is provided to allow a detailed inspection. To validate the effectiveness and usability of ACSeeker, we report two case studies and interviews with a social scientist and general researchers.",
"title": "Seek for Success: A Visualization Approach for Understanding the Dynamics of Academic Careers",
"normalizedTitle": "Seek for Success: A Visualization Approach for Understanding the Dynamics of Academic Careers",
"fno": "09552870",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Engineering Profession",
"Data Visualization",
"Social Factors",
"Visual Analytics",
"Collaboration",
"Sociology",
"Sequences",
"Career Analysis",
"Academic Profiles",
"Science Of Science",
"Publication Data",
"Citation Data",
"Sequence Analysis"
],
"authors": [
{
"givenName": "Yifang",
"surname": "Wang",
"fullName": "Yifang Wang",
"affiliation": "State Key Lab of CAD&CG, Zhejiang University and the Hong Kong University of Science and Technology, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Tai-Quan",
"surname": "Peng",
"fullName": "Tai-Quan Peng",
"affiliation": "Michigan State University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Huihua",
"surname": "Lu",
"fullName": "Huihua Lu",
"affiliation": "State Key Lab of CAD&CG, Zhejiang University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Haoren",
"surname": "Wang",
"fullName": "Haoren Wang",
"affiliation": "State Key Lab of CAD&CG, Zhejiang University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Xiao",
"surname": "Xie",
"fullName": "Xiao Xie",
"affiliation": "Department of Sport Science, Zhejiang University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Huamin",
"surname": "Qu",
"fullName": "Huamin Qu",
"affiliation": "Hong Kong University of Science and Technology, Hong Kong",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yingcai",
"surname": "Wu",
"fullName": "Yingcai Wu",
"affiliation": "State Key Lab of CAD&CG, Zhejiang University, China",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "475-485",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/fie/2015/8454/0/07344401",
"title": "Mapping career success competencies to engineering leadership capabilities",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2015/07344401/12OmNAXPyeJ",
"parentPublication": {
"id": "proceedings/fie/2015/8454/0",
"title": "2015 IEEE Frontiers in Education Conference (FIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fie/2011/468/0/06142881",
"title": "Examining the impact of mathematics identity on the choice of engineering careers for male and female students",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2011/06142881/12OmNxZBSAg",
"parentPublication": {
"id": "proceedings/fie/2011/468/0",
"title": "2011 Frontiers in Education Conference (FIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/respect/2016/3419/0/07836163",
"title": "Promoting computing faculty success through interinstitutional Faculty Learning Communities",
"doi": null,
"abstractUrl": "/proceedings-article/respect/2016/07836163/12OmNynsbu8",
"parentPublication": {
"id": "proceedings/respect/2016/3419/0",
"title": "2016 Research on Equity and Sustained Participation in Engineering, Computing, and Technology (RESPECT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iiai-aai/2017/0621/0/0621a001",
"title": "College Students Part-Time Jobs: Factors and Challenges for Future Careers",
"doi": null,
"abstractUrl": "/proceedings-article/iiai-aai/2017/0621a001/12OmNzTYBTV",
"parentPublication": {
"id": "proceedings/iiai-aai/2017/0621/0",
"title": "2017 6th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cs/2016/02/mcs2016020029",
"title": "Addressing Negative Racial and Gendered Experiences That Discourage Academic Careers in Engineering",
"doi": null,
"abstractUrl": "/magazine/cs/2016/02/mcs2016020029/13rRUygT7e4",
"parentPublication": {
"id": "mags/cs",
"title": "Computing in Science & Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fie/2018/1174/0/08659203",
"title": "Measuring Commuter Student Support and Success through Academic",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2018/08659203/18j9jCzw2WY",
"parentPublication": {
"id": "proceedings/fie/2018/1174/0",
"title": "2018 IEEE Frontiers in Education Conference (FIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/imitec/2021/1749/0/09714645",
"title": "The Influence of Clarity on Career Choice and Academic Success in First Year",
"doi": null,
"abstractUrl": "/proceedings-article/imitec/2021/09714645/1BaZGwCnrwI",
"parentPublication": {
"id": "proceedings/imitec/2021/1749/0",
"title": "2021 3rd International Multidisciplinary Information Technology and Engineering Conference (IMITEC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fie/2022/6244/0/09962687",
"title": "Gender differences in early careers of Finnish engineers",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2022/09962687/1IHnLpE7zcA",
"parentPublication": {
"id": "proceedings/fie/2022/6244/0",
"title": "2022 IEEE Frontiers in Education Conference (FIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ecit/2020/5902/0/590200a045",
"title": "The Relationship between Psychological Capital and Career Success of Internet E-Commerce Staff: Analysis of Chain Mediating Effect",
"doi": null,
"abstractUrl": "/proceedings-article/ecit/2020/590200a045/1lgPJsKvMxq",
"parentPublication": {
"id": "proceedings/ecit/2020/5902/0",
"title": "2020 International Conference on E-Commerce and Internet Technology (ECIT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/10/09382844",
"title": "Interactive Visual Exploration of Longitudinal Historical Career Mobility Data",
"doi": null,
"abstractUrl": "/journal/tg/2022/10/09382844/1saZr0JHX5C",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552205",
"articleId": "1xic4zmtlra",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552447",
"articleId": "1xic0dHxM9a",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBb2j4KrFS",
"name": "ttg202201-09552870s1-supp2-3114790.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552870s1-supp2-3114790.pdf",
"extension": "pdf",
"size": "265 kB",
"__typename": "WebExtraType"
},
{
"id": "1zBb2x0edm8",
"name": "ttg202201-09552870s1-supp1-3114790.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552870s1-supp1-3114790.mp4",
"extension": "mp4",
"size": "29.2 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xic0dHxM9a",
"doi": "10.1109/TVCG.2021.3114820",
"abstract": "There are a few prominent practices for conducting reviews of academic literature, including searching for specific keywords on Google Scholar or checking citations from some initial seed paper(s). These approaches serve a critical purpose for academic literature reviews, yet there remain challenges in identifying relevant literature when similar work may utilize different terminology (e.g., mixed-initiative visual analytics papers may not use the same terminology as papers on model-steering, yet the two topics are relevant to one another). In this paper, we introduce a system, VITALITY, intended to complement existing practices. In particular, VITALITY promotes serendipitous discovery of relevant literature using transformer language models, allowing users to find semantically similar papers in a word embedding space given (1) a list of input paper(s) or (2) a working abstract. VITALITY visualizes this document-level embedding space in an interactive 2-D scatterplot using dimension reduction. VITALITY also summarizes meta information about the document corpus or search query, including keywords and co-authors, and allows users to save and export papers for use in a literature review. We present qualitative findings from an evaluation of VITALITY, suggesting it can be a promising complementary technique for conducting academic literature reviews. Furthermore, we contribute data from 38 popular data visualization publication venues in VITALITY, and we provide scrapers for the open-source community to continue to grow the list of supported venues.",
"abstracts": [
{
"abstractType": "Regular",
"content": "There are a few prominent practices for conducting reviews of academic literature, including searching for specific keywords on Google Scholar or checking citations from some initial seed paper(s). These approaches serve a critical purpose for academic literature reviews, yet there remain challenges in identifying relevant literature when similar work may utilize different terminology (e.g., mixed-initiative visual analytics papers may not use the same terminology as papers on model-steering, yet the two topics are relevant to one another). In this paper, we introduce a system, VITALITY, intended to complement existing practices. In particular, VITALITY promotes serendipitous discovery of relevant literature using transformer language models, allowing users to find semantically similar papers in a word embedding space given (1) a list of input paper(s) or (2) a working abstract. VITALITY visualizes this document-level embedding space in an interactive 2-D scatterplot using dimension reduction. VITALITY also summarizes meta information about the document corpus or search query, including keywords and co-authors, and allows users to save and export papers for use in a literature review. We present qualitative findings from an evaluation of VITALITY, suggesting it can be a promising complementary technique for conducting academic literature reviews. Furthermore, we contribute data from 38 popular data visualization publication venues in VITALITY, and we provide scrapers for the open-source community to continue to grow the list of supported venues.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "There are a few prominent practices for conducting reviews of academic literature, including searching for specific keywords on Google Scholar or checking citations from some initial seed paper(s). These approaches serve a critical purpose for academic literature reviews, yet there remain challenges in identifying relevant literature when similar work may utilize different terminology (e.g., mixed-initiative visual analytics papers may not use the same terminology as papers on model-steering, yet the two topics are relevant to one another). In this paper, we introduce a system, VITALITY, intended to complement existing practices. In particular, VITALITY promotes serendipitous discovery of relevant literature using transformer language models, allowing users to find semantically similar papers in a word embedding space given (1) a list of input paper(s) or (2) a working abstract. VITALITY visualizes this document-level embedding space in an interactive 2-D scatterplot using dimension reduction. VITALITY also summarizes meta information about the document corpus or search query, including keywords and co-authors, and allows users to save and export papers for use in a literature review. We present qualitative findings from an evaluation of VITALITY, suggesting it can be a promising complementary technique for conducting academic literature reviews. Furthermore, we contribute data from 38 popular data visualization publication venues in VITALITY, and we provide scrapers for the open-source community to continue to grow the list of supported venues.",
"title": "VITALITY: Promoting Serendipitous Discovery of Academic Literature with Transformers & Visual Analytics",
"normalizedTitle": "VITALITY: Promoting Serendipitous Discovery of Academic Literature with Transformers & Visual Analytics",
"fno": "09552447",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Bibliographies",
"Data Visualization",
"Transformers",
"Keyword Search",
"Internet",
"Tools",
"Visual Analytics",
"Transformers",
"Word Embeddings",
"Literature Review",
"Web Scraper",
"Dataset",
"Visual Analytics"
],
"authors": [
{
"givenName": "Arpit",
"surname": "Narechania",
"fullName": "Arpit Narechania",
"affiliation": "Georgia Tech., United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Alireza",
"surname": "Karduni",
"fullName": "Alireza Karduni",
"affiliation": "UNC-Charlotte, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Ryan",
"surname": "Wesslen",
"fullName": "Ryan Wesslen",
"affiliation": "UNC-Charlotte, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Emily",
"surname": "Wall",
"fullName": "Emily Wall",
"affiliation": "Emory University, United States",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "486-496",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/seaa/2016/2820/0/2820a181",
"title": "Literature Review of Empirical Research Studies within the Domain of Acceptance Testing",
"doi": null,
"abstractUrl": "/proceedings-article/seaa/2016/2820a181/12OmNAu1Fky",
"parentPublication": {
"id": "proceedings/seaa/2016/2820/0",
"title": "2016 42th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ecodim/2003/8590/0/01322643",
"title": "Electronics ecodesign research empirically studied",
"doi": null,
"abstractUrl": "/proceedings-article/ecodim/2003/01322643/12OmNyTwRhp",
"parentPublication": {
"id": "proceedings/ecodim/2003/8590/0",
"title": "2003. 3rd International Symposium on Environmentally Conscious Design and Inverse Manufacturing - EcoDesign'03",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/2018/05/mcg2018050038",
"title": "VitalVizor: A Visual Analytics System for Studying Urban Vitality",
"doi": null,
"abstractUrl": "/magazine/cg/2018/05/mcg2018050038/13WBGNxhc5X",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2013/07/ttg2013071076",
"title": "Guest Editors' Introduction: Special Section on the IEEE Conference on Visual Analytics Science and Technology (VAST)",
"doi": null,
"abstractUrl": "/journal/tg/2013/07/ttg2013071076/13rRUxOdD2D",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/eitt/2021/2757/0/275700a346",
"title": "The Application of Physiological Feedback to the Evaluation of Academic Emotion: A Literature Review",
"doi": null,
"abstractUrl": "/proceedings-article/eitt/2021/275700a346/1AFsp4BQj5e",
"parentPublication": {
"id": "proceedings/eitt/2021/2757/0",
"title": "2021 Tenth International Conference of Educational Innovation through Technology (EITT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fie/2022/6244/0/09962393",
"title": "Analysis of Academic Databases for Literature Review in the Computer Science Education Field",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2022/09962393/1IHoj3gGzCM",
"parentPublication": {
"id": "proceedings/fie/2022/6244/0",
"title": "2022 IEEE Frontiers in Education Conference (FIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/10081322",
"title": "How Does Attention Work in Vision Transformers? A Visual Analytics Attempt",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/10081322/1LRbRtJhrG0",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fie/2020/8961/0/09274264",
"title": "Literature Review on Work-Based Learning",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2020/09274264/1phRM7OWAiA",
"parentPublication": {
"id": "proceedings/fie/2020/8961/0",
"title": "2020 IEEE Frontiers in Education Conference (FIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/respect/2020/7172/1/09272481",
"title": "Educational Initiatives to Retain Hispanic/Latinx Students in Computing: A Systematic Literature Mapping",
"doi": null,
"abstractUrl": "/proceedings-article/respect/2020/09272481/1phRZURR8XK",
"parentPublication": {
"id": "proceedings/respect/2020/7172/1",
"title": "2020 Research on Equity and Sustained Participation in Engineering, Computing, and Technology (RESPECT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/01/09552238",
"title": "What's the Situation with Situated Visualization? A Survey and Perspectives on Situatedness",
"doi": null,
"abstractUrl": "/journal/tg/2022/01/09552238/1xic77YygOk",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552870",
"articleId": "1xic90zZWDu",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552840",
"articleId": "1xic2GL1FC0",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBaAJFMKZi",
"name": "ttg202201-09552447s1-supp1-3114820.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552447s1-supp1-3114820.mp4",
"extension": "mp4",
"size": "13.7 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xic2GL1FC0",
"doi": "10.1109/TVCG.2021.3114787",
"abstract": "We present an exploratory analysis of gender representation among the authors, committee members, and award winners at the IEEE Visualization (VIS) conference over the last 30 years. Our goal is to provide descriptive data on which diversity discussions and efforts in the community can build. We look in particular at the gender of VIS authors as a proxy for the community at large. We consider measures of overall gender representation among authors, differences in careers, positions in author lists, and collaborations. We found that the proportion of female authors has increased from 9% in the first five years to 22% in the last five years of the conference. Over the years, we found the same representation of women in program committees and slightly more women in organizing committees. Women are less likely to appear in the last author position, but more in the middle positions. In terms of collaboration patterns, female authors tend to collaborate more than expected with other women in the community. All non-gender related data is available on https://osf.io/ydfj4/ and the gender-author matching can be accessed through https://nyu.databrary.org/volume/1301.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We present an exploratory analysis of gender representation among the authors, committee members, and award winners at the IEEE Visualization (VIS) conference over the last 30 years. Our goal is to provide descriptive data on which diversity discussions and efforts in the community can build. We look in particular at the gender of VIS authors as a proxy for the community at large. We consider measures of overall gender representation among authors, differences in careers, positions in author lists, and collaborations. We found that the proportion of female authors has increased from 9% in the first five years to 22% in the last five years of the conference. Over the years, we found the same representation of women in program committees and slightly more women in organizing committees. Women are less likely to appear in the last author position, but more in the middle positions. In terms of collaboration patterns, female authors tend to collaborate more than expected with other women in the community. All non-gender related data is available on https://osf.io/ydfj4/ and the gender-author matching can be accessed through https://nyu.databrary.org/volume/1301.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We present an exploratory analysis of gender representation among the authors, committee members, and award winners at the IEEE Visualization (VIS) conference over the last 30 years. Our goal is to provide descriptive data on which diversity discussions and efforts in the community can build. We look in particular at the gender of VIS authors as a proxy for the community at large. We consider measures of overall gender representation among authors, differences in careers, positions in author lists, and collaborations. We found that the proportion of female authors has increased from 9% in the first five years to 22% in the last five years of the conference. Over the years, we found the same representation of women in program committees and slightly more women in organizing committees. Women are less likely to appear in the last author position, but more in the middle positions. In terms of collaboration patterns, female authors tend to collaborate more than expected with other women in the community. All non-gender related data is available on https://osf.io/ydfj4/ and the gender-author matching can be accessed through https://nyu.databrary.org/volume/1301.",
"title": "Gender in 30 Years of IEEE Visualization",
"normalizedTitle": "Gender in 30 Years of IEEE Visualization",
"fno": "09552840",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Engineering Profession",
"Data Visualization",
"Manuals",
"Conferences",
"Collaboration",
"Cleaning",
"Gender Issues",
"Visualization",
"Gender",
"Diversity",
"Publication",
"Scientometry",
"Collaboration"
],
"authors": [
{
"givenName": "Natkamon",
"surname": "Tovanich",
"fullName": "Natkamon Tovanich",
"affiliation": "IRT SystemX, Paris-Saclay, Palaiseau, France",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Pierre",
"surname": "Dragicevic",
"fullName": "Pierre Dragicevic",
"affiliation": "Université Paris-Saclay, CNRS, Inria, LISN, Orsay, France",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Petra",
"surname": "Isenberg",
"fullName": "Petra Isenberg",
"affiliation": "Université Paris-Saclay, CNRS, Inria, LISN, Orsay, France",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "497-507",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/fie/2006/0256/0/04117062",
"title": "\"You're all a bunch of fucking feminists:\" Addressing the perceived conflict between gender and professional identities using the Montreal Massacre",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2006/04117062/12OmNzVoBAd",
"parentPublication": {
"id": "proceedings/fie/2006/0256/0",
"title": "Proceedings. Frontiers in Education. 36th Annual Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/ex/2016/04/mex2016040062",
"title": "What Men Say, What Women Hear: Finding Gender-Specific Meaning Shades",
"doi": null,
"abstractUrl": "/magazine/ex/2016/04/mex2016040062/13rRUxBJhj6",
"parentPublication": {
"id": "mags/ex",
"title": "IEEE Intelligent Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09733942",
"title": "Scientometric Analysis of Interdisciplinary Collaboration and Gender Trends in 30 Years of IEEE VIS Publications",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09733942/1BJIbG1OGqc",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fie/2022/6244/0/09962687",
"title": "Gender differences in early careers of Finnish engineers",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2022/09962687/1IHnLpE7zcA",
"parentPublication": {
"id": "proceedings/fie/2022/6244/0",
"title": "2022 IEEE Frontiers in Education Conference (FIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/sp/2019/04/08755960",
"title": "Toward Gender-Equitable Privacy and Security in South Asia",
"doi": null,
"abstractUrl": "/magazine/sp/2019/04/08755960/1bojOWk4jMQ",
"parentPublication": {
"id": "mags/sp",
"title": "IEEE Security & Privacy",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ge/2019/2245/0/224500a021",
"title": "Gender Disparity in the Governance of Software Engineering Conferences",
"doi": null,
"abstractUrl": "/proceedings-article/ge/2019/224500a021/1cTJejsHBCM",
"parentPublication": {
"id": "proceedings/ge/2019/2245/0",
"title": "2019 IEEE/ACM 2nd International Workshop on Gender Equality in Software Engineering (GE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/so/2019/06/08880051",
"title": "Gender in Software Engineering",
"doi": null,
"abstractUrl": "/magazine/so/2019/06/08880051/1ekTayi7kt2",
"parentPublication": {
"id": "mags/so",
"title": "IEEE Software",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/so/2021/02/09261329",
"title": "Gender Differences in Public Code Contributions: A 50-Year Perspective",
"doi": null,
"abstractUrl": "/magazine/so/2021/02/09261329/1oPzR4iA4nu",
"parentPublication": {
"id": "mags/so",
"title": "IEEE Software",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isaiee/2020/5668/0/566800a087",
"title": "Feasibility of Gender Equality in Academic Research Based on STS Concept",
"doi": null,
"abstractUrl": "/proceedings-article/isaiee/2020/566800a087/1sQKh69qBG0",
"parentPublication": {
"id": "proceedings/isaiee/2020/5668/0",
"title": "2020 International Symposium on Advances in Informatics, Electronics and Education (ISAIEE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/respect/2021/4905/0/09620659",
"title": "CS1 Students' Perspectives on the Computer Science Gender Gap: Achieving Equity Requires Awareness",
"doi": null,
"abstractUrl": "/proceedings-article/respect/2021/09620659/1yXuIb7pwKk",
"parentPublication": {
"id": "proceedings/respect/2021/4905/0",
"title": "2021 Conference on Research in Equitable and Sustained Participation in Engineering, Computing, and Technology (RESPECT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552447",
"articleId": "1xic0dHxM9a",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09555490",
"articleId": "1xjR3LSQrLi",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xjR3LSQrLi",
"doi": "10.1109/TVCG.2021.3114789",
"abstract": "What makes speeches effective has long been a subject for debate, and until today there is broad controversy among public speaking experts about what factors make a speech effective as well as the roles of these factors in speeches. Moreover, there is a lack of quantitative analysis methods to help understand effective speaking strategies. In this paper, we propose E-ffective, a visual analytic system allowing speaking experts and novices to analyze both the role of speech factors and their contribution in effective speeches. From interviews with domain experts and investigating existing literature, we identified important factors to consider in inspirational speeches. We obtained the generated factors from multi-modal data that were then related to effectiveness data. Our system supports rapid understanding of critical factors in inspirational speeches, including the influence of emotions by means of novel visualization methods and interaction. Two novel visualizations include E-spiral (that shows the emotional shifts in speeches in a visually compact way) and E-script (that connects speech content with key speech delivery information). In our evaluation we studied the influence of our system on experts' domain knowledge about speech factors. We further studied the usability of the system by speaking novices and experts on assisting analysis of inspirational speech effectiveness.",
"abstracts": [
{
"abstractType": "Regular",
"content": "What makes speeches effective has long been a subject for debate, and until today there is broad controversy among public speaking experts about what factors make a speech effective as well as the roles of these factors in speeches. Moreover, there is a lack of quantitative analysis methods to help understand effective speaking strategies. In this paper, we propose E-ffective, a visual analytic system allowing speaking experts and novices to analyze both the role of speech factors and their contribution in effective speeches. From interviews with domain experts and investigating existing literature, we identified important factors to consider in inspirational speeches. We obtained the generated factors from multi-modal data that were then related to effectiveness data. Our system supports rapid understanding of critical factors in inspirational speeches, including the influence of emotions by means of novel visualization methods and interaction. Two novel visualizations include E-spiral (that shows the emotional shifts in speeches in a visually compact way) and E-script (that connects speech content with key speech delivery information). In our evaluation we studied the influence of our system on experts' domain knowledge about speech factors. We further studied the usability of the system by speaking novices and experts on assisting analysis of inspirational speech effectiveness.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "What makes speeches effective has long been a subject for debate, and until today there is broad controversy among public speaking experts about what factors make a speech effective as well as the roles of these factors in speeches. Moreover, there is a lack of quantitative analysis methods to help understand effective speaking strategies. In this paper, we propose E-ffective, a visual analytic system allowing speaking experts and novices to analyze both the role of speech factors and their contribution in effective speeches. From interviews with domain experts and investigating existing literature, we identified important factors to consider in inspirational speeches. We obtained the generated factors from multi-modal data that were then related to effectiveness data. Our system supports rapid understanding of critical factors in inspirational speeches, including the influence of emotions by means of novel visualization methods and interaction. Two novel visualizations include E-spiral (that shows the emotional shifts in speeches in a visually compact way) and E-script (that connects speech content with key speech delivery information). In our evaluation we studied the influence of our system on experts' domain knowledge about speech factors. We further studied the usability of the system by speaking novices and experts on assisting analysis of inspirational speech effectiveness.",
"title": "E-ffective: A Visual Analytic System for Exploring the Emotion and Effectiveness of Inspirational Speeches",
"normalizedTitle": "E-ffective: A Visual Analytic System for Exploring the Emotion and Effectiveness of Inspirational Speeches",
"fno": "09555490",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Data Analysis",
"Data Visualisation",
"Speech Recognition",
"Speech Content",
"Key Speech Delivery Information",
"Speech Factors",
"Inspirational Speech Effectiveness",
"Visual Analytic System",
"Inspirational Speeches",
"Public Speaking Experts",
"Speech Effective",
"Quantitative Analysis Methods",
"Effective Speaking Strategies",
"Effective Speeches",
"Domain Experts",
"Investigating Existing Literature",
"Generated Factors",
"Effectiveness Data",
"Novel Visualization Methods",
"Speech",
"Public Speaking",
"Interviews",
"Measurement",
"Data Visualization",
"Visual Analytics",
"Task Analysis",
"Affective Visualization",
"Multimodal Analysis",
"Speech Effectiveness"
],
"authors": [
{
"givenName": "Kevin",
"surname": "Maher",
"fullName": "Kevin Maher",
"affiliation": "Institute of Software, Chinese Academy of Sciences, Tsinghua University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Zeyuan",
"surname": "Huang",
"fullName": "Zeyuan Huang",
"affiliation": "State Key Laboratory of Computer Science, Beijing Key Lab of Human-Computer Interaction, Institute of Software, Chinese Academy of Sciences, University of Chinese Academy of Sciences, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jiancheng",
"surname": "Song",
"fullName": "Jiancheng Song",
"affiliation": "State Key Laboratory of Computer Science, Beijing Key Lab of Human-Computer Interaction, Institute of Software, Chinese Academy of Sciences, University of Chinese Academy of Sciences, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Xiaoming",
"surname": "Deng",
"fullName": "Xiaoming Deng",
"affiliation": "State Key Laboratory of Computer Science, Beijing Key Lab of Human-Computer Interaction, Institute of Software, Chinese Academy of Sciences, University of Chinese Academy of Sciences, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yu-Kun",
"surname": "Lai",
"fullName": "Yu-Kun Lai",
"affiliation": "Cardiff University, United Kingdom",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Cuixia",
"surname": "Ma",
"fullName": "Cuixia Ma",
"affiliation": "State Key Laboratory of Computer Science, Beijing Key Lab of Human-Computer Interaction, Institute of Software, Chinese Academy of Sciences, University of Chinese Academy of Sciences, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Hao",
"surname": "Wang",
"fullName": "Hao Wang",
"affiliation": "State Key Laboratory of Computer Science, Beijing Key Lab of Human-Computer Interaction, Institute of Software, Chinese Academy of Sciences, University of Chinese Academy of Sciences, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yong-Jin",
"surname": "Liu",
"fullName": "Yong-Jin Liu",
"affiliation": "Tsinghua University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Hongan",
"surname": "Wang",
"fullName": "Hongan Wang",
"affiliation": "Alibaba Group, China",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "508-517",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/vr/2013/4795/0/06549363",
"title": "Virtual audience customization for public speaking training procedures",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2013/06549363/12OmNAq3hG7",
"parentPublication": {
"id": "proceedings/vr/2013/4795/0",
"title": "2013 IEEE Virtual Reality (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fg/2018/2335/0/233501a607",
"title": "Analyzing the Impact of Gender on the Automation of Feedback for Public Speaking",
"doi": null,
"abstractUrl": "/proceedings-article/fg/2018/233501a607/12OmNBt3qna",
"parentPublication": {
"id": "proceedings/fg/2018/2335/0",
"title": "2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icis/2016/0806/0/07550793",
"title": "Head pose estimation and movement analysis for speech scene",
"doi": null,
"abstractUrl": "/proceedings-article/icis/2016/07550793/12OmNrH1PFd",
"parentPublication": {
"id": "proceedings/icis/2016/0806/0",
"title": "2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/t4e/2015/9509/0/9509a109",
"title": "Technology Enabled Learning (TEL) to Improve Pronunciation in the Students of Professional Courses -- A Study",
"doi": null,
"abstractUrl": "/proceedings-article/t4e/2015/9509a109/12OmNyvGygs",
"parentPublication": {
"id": "proceedings/t4e/2015/9509/0",
"title": "2015 IEEE Seventh International Conference on Technology for Education (T4E)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bigcomp/2019/7789/0/08679261",
"title": "SpeechLens: A Visual Analytics Approach for Exploring Speech Strategies with Textural and Acoustic Features",
"doi": null,
"abstractUrl": "/proceedings-article/bigcomp/2019/08679261/18XknOkGKbK",
"parentPublication": {
"id": "proceedings/bigcomp/2019/7789/0",
"title": "2019 IEEE International Conference on Big Data and Smart Computing (BigComp)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09761750",
"title": "GestureLens: Visual Analysis of Gestures in Presentation Videos",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09761750/1CKMkYw5fa0",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/ta/2022/01/08818609",
"title": "Affective Audio Annotation of Public Speeches with Convolutional Clustering Neural Network",
"doi": null,
"abstractUrl": "/journal/ta/2022/01/08818609/1cRBn0C8oCc",
"parentPublication": {
"id": "trans/ta",
"title": "IEEE Transactions on Affective Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vrw/2020/6532/0/09090563",
"title": "Virtualized Speech Practice for the College Classroom",
"doi": null,
"abstractUrl": "/proceedings-article/vrw/2020/09090563/1jIxutrshaw",
"parentPublication": {
"id": "proceedings/vrw/2020/6532/0",
"title": "2020 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wi-iat/2020/1924/0/192400a724",
"title": "An Analysis of Interpersonal Function in TED Educational Speeches",
"doi": null,
"abstractUrl": "/proceedings-article/wi-iat/2020/192400a724/1uHhsnJt5CM",
"parentPublication": {
"id": "proceedings/wi-iat/2020/1924/0",
"title": "2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/12/09488285",
"title": "DeHumor: Visual Analytics for Decomposing Humor",
"doi": null,
"abstractUrl": "/journal/tg/2022/12/09488285/1vhIcg5WCZy",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552840",
"articleId": "1xic2GL1FC0",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552910",
"articleId": "1xicaDADRqU",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBaYJznOus",
"name": "ttg202201-09555490s1-supp1-3114789.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09555490s1-supp1-3114789.mp4",
"extension": "mp4",
"size": "119 MB",
"__typename": "WebExtraType"
},
{
"id": "1zBaYxqTcFq",
"name": "ttg202201-09555490s1-supp2-3114789.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09555490s1-supp2-3114789.pdf",
"extension": "pdf",
"size": "991 kB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xicaDADRqU",
"doi": "10.1109/TVCG.2021.3114818",
"abstract": "Administrative justice concerns the relationships between individuals and the state. It includes redress and complaints on decisions of a child's education, social care, licensing, planning, environment, housing and homelessness. However, if someone has a complaint or an issue, it is challenging for people to understand different possible redress paths and explore what path is suitable for their situation. Explanatory visualisation has the potential to display these paths of redress in a clear way, such that people can see, understand and explore their options. The visualisation challenge is further complicated because information is spread across many documents, laws, guidance and policies and requires judicial interpretation. Consequently, there is not a single database of paths of redress. In this work we present how we have co-designed a system to visualise administrative justice paths of redress. Simultaneously, we classify, collate and organise the underpinning data, from expert workshops, heuristic evaluation and expert critical reflection. We make four contributions: (i) an application design study of the explanatory visualisation tool (Artemus), (ii) coordinated and co-design approach to aggregating the data, (iii) two in-depth case studies in housing and education demonstrating explanatory paths of redress in administrative law, and (iv) reflections on the expert co-design process and expert data gathering and explanatory visualisation for administrative justice and law.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Administrative justice concerns the relationships between individuals and the state. It includes redress and complaints on decisions of a child's education, social care, licensing, planning, environment, housing and homelessness. However, if someone has a complaint or an issue, it is challenging for people to understand different possible redress paths and explore what path is suitable for their situation. Explanatory visualisation has the potential to display these paths of redress in a clear way, such that people can see, understand and explore their options. The visualisation challenge is further complicated because information is spread across many documents, laws, guidance and policies and requires judicial interpretation. Consequently, there is not a single database of paths of redress. In this work we present how we have co-designed a system to visualise administrative justice paths of redress. Simultaneously, we classify, collate and organise the underpinning data, from expert workshops, heuristic evaluation and expert critical reflection. We make four contributions: (i) an application design study of the explanatory visualisation tool (Artemus), (ii) coordinated and co-design approach to aggregating the data, (iii) two in-depth case studies in housing and education demonstrating explanatory paths of redress in administrative law, and (iv) reflections on the expert co-design process and expert data gathering and explanatory visualisation for administrative justice and law.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Administrative justice concerns the relationships between individuals and the state. It includes redress and complaints on decisions of a child's education, social care, licensing, planning, environment, housing and homelessness. However, if someone has a complaint or an issue, it is challenging for people to understand different possible redress paths and explore what path is suitable for their situation. Explanatory visualisation has the potential to display these paths of redress in a clear way, such that people can see, understand and explore their options. The visualisation challenge is further complicated because information is spread across many documents, laws, guidance and policies and requires judicial interpretation. Consequently, there is not a single database of paths of redress. In this work we present how we have co-designed a system to visualise administrative justice paths of redress. Simultaneously, we classify, collate and organise the underpinning data, from expert workshops, heuristic evaluation and expert critical reflection. We make four contributions: (i) an application design study of the explanatory visualisation tool (Artemus), (ii) coordinated and co-design approach to aggregating the data, (iii) two in-depth case studies in housing and education demonstrating explanatory paths of redress in administrative law, and (iv) reflections on the expert co-design process and expert data gathering and explanatory visualisation for administrative justice and law.",
"title": "Explanatory Journeys: Visualising to Understand and Explain Administrative Justice Paths of Redress",
"normalizedTitle": "Explanatory Journeys: Visualising to Understand and Explain Administrative Justice Paths of Redress",
"fno": "09552910",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Data Visualization",
"Law",
"Visualization",
"Conferences",
"Tools",
"Education",
"Navigation",
"Explanatory Visualisation",
"Administrative Justice",
"Law",
"Law Visualisation"
],
"authors": [
{
"givenName": "Jonathan C.",
"surname": "Roberts",
"fullName": "Jonathan C. Roberts",
"affiliation": "Bangor University, United Kingdom",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Peter",
"surname": "Butcher",
"fullName": "Peter Butcher",
"affiliation": "Bangor University, United Kingdom",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Ann",
"surname": "Sherlock",
"fullName": "Ann Sherlock",
"affiliation": "Bangor University, United Kingdom",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Sarah",
"surname": "Nason",
"fullName": "Sarah Nason",
"affiliation": "Bangor University, United Kingdom",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "518-528",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/ieee-infovis/1995/7201/0/72010090",
"title": "Case study: Narcissus: visualising information",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-infovis/1995/72010090/12OmNwe2Iug",
"parentPublication": {
"id": "proceedings/ieee-infovis/1995/7201/0",
"title": "Information Visualization, IEEE Symposium on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2018/01/08017594",
"title": "The Explanatory Visualization Framework: An Active Learning Framework for Teaching Creative Computing Using Explanatory Visualizations",
"doi": null,
"abstractUrl": "/journal/tg/2018/01/08017594/13rRUyY28YC",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/itme/2018/7744/0/774400a688",
"title": "A Mobile Tool for Interactive Visualisation of Genomics Data",
"doi": null,
"abstractUrl": "/proceedings-article/itme/2018/774400a688/17D45XdBRSw",
"parentPublication": {
"id": "proceedings/itme/2018/7744/0",
"title": "2018 9th International Conference on Information Technology in Medicine and Education (ITME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icedeg/2019/1704/0/08734366",
"title": "Analysing Dissenting Votes Through Electronic Justice From Online Posts to Streets: A Real Case",
"doi": null,
"abstractUrl": "/proceedings-article/icedeg/2019/08734366/1aPuYxCydaM",
"parentPublication": {
"id": "proceedings/icedeg/2019/1704/0",
"title": "2019 Sixth International Conference on eDemocracy & eGovernment (ICEDEG)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv-2/2019/2850/0/285000a042",
"title": "An Interactive Method for Visualising Physical Activity in Parks",
"doi": null,
"abstractUrl": "/proceedings-article/iv-2/2019/285000a042/1cMEPkhBBKw",
"parentPublication": {
"id": "proceedings/iv-2/2019/2850/0",
"title": "2019 23rd International Conference in Information Visualization – Part II",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv-2/2019/2850/0/285000a100",
"title": "Glossopticon: Visualising Archival Data",
"doi": null,
"abstractUrl": "/proceedings-article/iv-2/2019/285000a100/1cMEQNRefsY",
"parentPublication": {
"id": "proceedings/iv-2/2019/2850/0",
"title": "2019 23rd International Conference in Information Visualization – Part II",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2019/2838/0/283800a133",
"title": "Visual Analytics to Make Sense of Large-Scale Administrative and Normative Data",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2019/283800a133/1cMFavfKXqE",
"parentPublication": {
"id": "proceedings/iv/2019/2838/0",
"title": "2019 23rd International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icbdie/2021/3870/0/387000a692",
"title": "Research on Educational Reform of Administrative Law Based on Big Data",
"doi": null,
"abstractUrl": "/proceedings-article/icbdie/2021/387000a692/1uCiA2WUtRm",
"parentPublication": {
"id": "proceedings/icbdie/2021/3870/0",
"title": "2021 2nd International Conference on Big Data and Informatization Education (ICBDIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icaie/2021/2492/0/249200a076",
"title": "Responsible AI: The Revolution in Governance Technology in China",
"doi": null,
"abstractUrl": "/proceedings-article/icaie/2021/249200a076/1wV1Dl6aE6Y",
"parentPublication": {
"id": "proceedings/icaie/2021/2492/0",
"title": "2021 2nd International Conference on Artificial Intelligence and Education (ICAIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/respect/2021/4905/0/09620618",
"title": "Educational Programming Practices that Inspire Change: Social Justice as Situated in a Computer Programming Course",
"doi": null,
"abstractUrl": "/proceedings-article/respect/2021/09620618/1yXuIj7RXfa",
"parentPublication": {
"id": "proceedings/respect/2021/4905/0",
"title": "2021 Conference on Research in Equitable and Sustained Participation in Engineering, Computing, and Technology (RESPECT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09555490",
"articleId": "1xjR3LSQrLi",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552226",
"articleId": "1xicaXrIayI",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBb7TTJpde",
"name": "ttg202201-09552910s1-supp1-3114818.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552910s1-supp1-3114818.mp4",
"extension": "mp4",
"size": "4.43 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xicaXrIayI",
"doi": "10.1109/TVCG.2021.3114694",
"abstract": "Dimensionality Reduction (DR) techniques can generate 2D projections and enable visual exploration of cluster structures of high-dimensional datasets. However, different DR techniques would yield various patterns, which significantly affect the performance of visual cluster analysis tasks. We present the results of a user study that investigates the influence of different DR techniques on visual cluster analysis. Our study focuses on the most concerned property types, namely the linearity and locality, and evaluates twelve representative DR techniques that cover the concerned properties. Four controlled experiments were conducted to evaluate how the DR techniques facilitate the tasks of 1) cluster identification, 2) membership identification, 3) distance comparison, and 4) density comparison, respectively. We also evaluated users' subjective preference of the DR techniques regarding the quality of projected clusters. The results show that: 1) Non-linear and Local techniques are preferred in cluster identification and membership identification; 2) Linear techniques perform better than non-linear techniques in density comparison; 3) UMAP (Uniform Manifold Approximation and Projection) and t-SNE (t-Distributed Stochastic Neighbor Embedding) perform the best in cluster identification and membership identification; 4) NMF (Nonnegative Matrix Factorization) has competitive performance in distance comparison; 5) t-SNLE (t-Distributed Stochastic Neighbor Linear Embedding) has competitive performance in density comparison.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Dimensionality Reduction (DR) techniques can generate 2D projections and enable visual exploration of cluster structures of high-dimensional datasets. However, different DR techniques would yield various patterns, which significantly affect the performance of visual cluster analysis tasks. We present the results of a user study that investigates the influence of different DR techniques on visual cluster analysis. Our study focuses on the most concerned property types, namely the linearity and locality, and evaluates twelve representative DR techniques that cover the concerned properties. Four controlled experiments were conducted to evaluate how the DR techniques facilitate the tasks of 1) cluster identification, 2) membership identification, 3) distance comparison, and 4) density comparison, respectively. We also evaluated users' subjective preference of the DR techniques regarding the quality of projected clusters. The results show that: 1) Non-linear and Local techniques are preferred in cluster identification and membership identification; 2) Linear techniques perform better than non-linear techniques in density comparison; 3) UMAP (Uniform Manifold Approximation and Projection) and t-SNE (t-Distributed Stochastic Neighbor Embedding) perform the best in cluster identification and membership identification; 4) NMF (Nonnegative Matrix Factorization) has competitive performance in distance comparison; 5) t-SNLE (t-Distributed Stochastic Neighbor Linear Embedding) has competitive performance in density comparison.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Dimensionality Reduction (DR) techniques can generate 2D projections and enable visual exploration of cluster structures of high-dimensional datasets. However, different DR techniques would yield various patterns, which significantly affect the performance of visual cluster analysis tasks. We present the results of a user study that investigates the influence of different DR techniques on visual cluster analysis. Our study focuses on the most concerned property types, namely the linearity and locality, and evaluates twelve representative DR techniques that cover the concerned properties. Four controlled experiments were conducted to evaluate how the DR techniques facilitate the tasks of 1) cluster identification, 2) membership identification, 3) distance comparison, and 4) density comparison, respectively. We also evaluated users' subjective preference of the DR techniques regarding the quality of projected clusters. The results show that: 1) Non-linear and Local techniques are preferred in cluster identification and membership identification; 2) Linear techniques perform better than non-linear techniques in density comparison; 3) UMAP (Uniform Manifold Approximation and Projection) and t-SNE (t-Distributed Stochastic Neighbor Embedding) perform the best in cluster identification and membership identification; 4) NMF (Nonnegative Matrix Factorization) has competitive performance in distance comparison; 5) t-SNLE (t-Distributed Stochastic Neighbor Linear Embedding) has competitive performance in density comparison.",
"title": "Revisiting Dimensionality Reduction Techniques for Visual Cluster Analysis: An Empirical Study",
"normalizedTitle": "Revisiting Dimensionality Reduction Techniques for Visual Cluster Analysis: An Empirical Study",
"fno": "09552226",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Approximation Theory",
"Data Analysis",
"Data Reduction",
"Data Visualisation",
"Eigenvalues And Eigenfunctions",
"Learning Artificial Intelligence",
"Matrix Decomposition",
"Pattern Clustering",
"Stochastic Processes",
"Dimensionality Reduction Techniques",
"Visual Exploration",
"Cluster Structures",
"High Dimensional Datasets",
"Different DR Techniques",
"Visual Cluster Analysis Tasks",
"Concerned Property Types",
"Representative DR Techniques",
"Concerned Properties",
"Users",
"Projected Clusters",
"Local Techniques",
"Cluster Identification",
"Membership Identification",
"Nonlinear Techniques",
"Density Comparison",
"Competitive Performance",
"T Distributed Stochastic Neighbor Linear Embedding",
"Visualization",
"Task Analysis",
"Principal Component Analysis",
"Measurement",
"Manifolds",
"Linearity",
"Visual Perception",
"Dimensionality Reduction",
"Visual Cluster Analysis",
"Perception Based Evaluation"
],
"authors": [
{
"givenName": "Jiazhi",
"surname": "Xia",
"fullName": "Jiazhi Xia",
"affiliation": "School of Computer Science and Engineering, Central South University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yuchen",
"surname": "Zhang",
"fullName": "Yuchen Zhang",
"affiliation": "School of Computer Science and Engineering, Central South University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jie",
"surname": "Song",
"fullName": "Jie Song",
"affiliation": "School of Computer Science and Engineering, Central South University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yang",
"surname": "Chen",
"fullName": "Yang Chen",
"affiliation": "I4 data, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yunhai",
"surname": "Wang",
"fullName": "Yunhai Wang",
"affiliation": "School of Computer Science and Technology, Shandong University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Shixia",
"surname": "Liu",
"fullName": "Shixia Liu",
"affiliation": "School of Software, Tsinghua University, China",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "529-539",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/iv/2013/5049/0/5049a174",
"title": "Nonlinear Dimensionality Reduction for Cluster Identification in Metagenomic Samples",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2013/5049a174/12OmNARRYzB",
"parentPublication": {
"id": "proceedings/iv/2013/5049/0",
"title": "2013 17th International Conference on Information Visualisation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdar/2013/4999/0/06628827",
"title": "An Empirical Evaluation of Supervised Dimensionality Reduction for Recognition",
"doi": null,
"abstractUrl": "/proceedings-article/icdar/2013/06628827/12OmNApu5Ku",
"parentPublication": {
"id": "proceedings/icdar/2013/4999/0",
"title": "2013 12th International Conference on Document Analysis and Recognition (ICDAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2013/0015/0/06607550",
"title": "Nonlinear dimensionality reduction approaches applied to music and textural sounds",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2013/06607550/12OmNrAdsvq",
"parentPublication": {
"id": "proceedings/icme/2013/0015/0",
"title": "2013 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2013/12/ttg2013122634",
"title": "Empirical Guidance on Scatterplot and Dimension Reduction Technique Choices",
"doi": null,
"abstractUrl": "/journal/tg/2013/12/ttg2013122634/13rRUEgs2BW",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09904480",
"title": "Interactive Visual Cluster Analysis by Contrastive Dimensionality Reduction",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09904480/1H0GkV5P1qo",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2020/01/08805461",
"title": "Supporting Analysis of Dimensionality Reduction Results with Contrastive Learning",
"doi": null,
"abstractUrl": "/journal/tg/2020/01/08805461/1cG4ulCK5S8",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2019/2838/0/283800a228",
"title": "User-guided Dimensionality Reduction Ensembles",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2019/283800a228/1cMF9VUpFgA",
"parentPublication": {
"id": "proceedings/iv/2019/2838/0",
"title": "2019 23rd International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2022/04/09107495",
"title": "Dimensionality Reduction Based on Multilocal Linear Pattern Preservation",
"doi": null,
"abstractUrl": "/journal/tk/2022/04/09107495/1kmkvJGgz96",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vis/2020/8014/0/801400a111",
"title": "DRUID<inf>JS</inf> — A JavaScript Library for Dimensionality Reduction",
"doi": null,
"abstractUrl": "/proceedings-article/vis/2020/801400a111/1qRNP6eEG52",
"parentPublication": {
"id": "proceedings/vis/2020/8014/0",
"title": "2020 IEEE Visualization Conference (VIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/01/09555244",
"title": "Interactive Dimensionality Reduction for Comparative Analysis",
"doi": null,
"abstractUrl": "/journal/tg/2022/01/09555244/1xjR1QZtkTS",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552910",
"articleId": "1xicaDADRqU",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552929",
"articleId": "1xic3zJwVwI",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBb9c4hfUY",
"name": "ttg202201-09552226s1-supp1-3114694.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552226s1-supp1-3114694.pdf",
"extension": "pdf",
"size": "16.3 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xic3zJwVwI",
"doi": "10.1109/TVCG.2021.3114870",
"abstract": "Embeddings of high-dimensional data are widely used to explore data, to verify analysis results, and to communicate information. Their explanation, in particular with respect to the input attributes, is often difficult. With linear projects like PCA the axes can still be annotated meaningfully. With non-linear projections this is no longer possible and alternative strategies such as attribute-based color coding are required. In this paper, we review existing augmentation techniques and discuss their limitations. We present the Non-Linear Embeddings Surveyor (NoLiES) that combines a novel augmentation strategy for projected data (rangesets) with interactive analysis in a small multiples setting. Rangesets use a set-based visualization approach for binned attribute values that enable the user to quickly observe structure and detect outliers. We detail the link between algebraic topology and rangesets and demonstrate the utility of NoLiES in case studies with various challenges (complex attribute value distribution, many attributes, many data points) and a real-world application to understand latent features of matrix completion in thermodynamics.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Embeddings of high-dimensional data are widely used to explore data, to verify analysis results, and to communicate information. Their explanation, in particular with respect to the input attributes, is often difficult. With linear projects like PCA the axes can still be annotated meaningfully. With non-linear projections this is no longer possible and alternative strategies such as attribute-based color coding are required. In this paper, we review existing augmentation techniques and discuss their limitations. We present the Non-Linear Embeddings Surveyor (NoLiES) that combines a novel augmentation strategy for projected data (rangesets) with interactive analysis in a small multiples setting. Rangesets use a set-based visualization approach for binned attribute values that enable the user to quickly observe structure and detect outliers. We detail the link between algebraic topology and rangesets and demonstrate the utility of NoLiES in case studies with various challenges (complex attribute value distribution, many attributes, many data points) and a real-world application to understand latent features of matrix completion in thermodynamics.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Embeddings of high-dimensional data are widely used to explore data, to verify analysis results, and to communicate information. Their explanation, in particular with respect to the input attributes, is often difficult. With linear projects like PCA the axes can still be annotated meaningfully. With non-linear projections this is no longer possible and alternative strategies such as attribute-based color coding are required. In this paper, we review existing augmentation techniques and discuss their limitations. We present the Non-Linear Embeddings Surveyor (NoLiES) that combines a novel augmentation strategy for projected data (rangesets) with interactive analysis in a small multiples setting. Rangesets use a set-based visualization approach for binned attribute values that enable the user to quickly observe structure and detect outliers. We detail the link between algebraic topology and rangesets and demonstrate the utility of NoLiES in case studies with various challenges (complex attribute value distribution, many attributes, many data points) and a real-world application to understand latent features of matrix completion in thermodynamics.",
"title": "Attribute-based Explanation of Non-Linear Embeddings of High-Dimensional Data",
"normalizedTitle": "Attribute-based Explanation of Non-Linear Embeddings of High-Dimensional Data",
"fno": "09552929",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Data Visualization",
"Visualization",
"Task Analysis",
"Data Analysis",
"Topology",
"Image Color Analysis",
"Dimensionality Reduction",
"Embedding",
"Augmented Projections",
"Point Set Contours",
"Explainable Artificial Intelligence"
],
"authors": [
{
"givenName": "Jan-Tobias",
"surname": "Sohns",
"fullName": "Jan-Tobias Sohns",
"affiliation": "Visual Information Analysis group at TU Kaiserslautern, Germany",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Michaela",
"surname": "Schmitt",
"fullName": "Michaela Schmitt",
"affiliation": "Visual Information Analysis group at TU Kaiserslautern, Germany",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Fabian",
"surname": "Jirasek",
"fullName": "Fabian Jirasek",
"affiliation": "Laboratory of Engineering Thermodynamics (LTD) at TU Kaiserslautern, Germany",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Hans",
"surname": "Hasse",
"fullName": "Hans Hasse",
"affiliation": "Laboratory of Engineering Thermodynamics (LTD) at TU Kaiserslautern, Germany",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Heike",
"surname": "Leitte",
"fullName": "Heike Leitte",
"affiliation": "Visual Information Analysis group at TU Kaiserslautern, Germany",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "540-550",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/ieee-infovis/2003/2055/0/20550016",
"title": "Visualization of Labeled Data Using Linear Transformations",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-infovis/2003/20550016/12OmNyQGRZi",
"parentPublication": {
"id": "proceedings/ieee-infovis/2003/2055/0",
"title": "Information Visualization, IEEE Symposium on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2004/04/v0459",
"title": "Robust Linear Dimensionality Reduction",
"doi": null,
"abstractUrl": "/journal/tg/2004/04/v0459/13rRUxBJhFl",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pacificvis/2022/2335/0/233500a011",
"title": "Incorporating Texture Information into Dimensionality Reduction for High-Dimensional Images",
"doi": null,
"abstractUrl": "/proceedings-article/pacificvis/2022/233500a011/1E2wiOFBEbe",
"parentPublication": {
"id": "proceedings/pacificvis/2022/2335/0",
"title": "2022 IEEE 15th Pacific Visualization Symposium (PacificVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09903343",
"title": "RankAxis: Towards a Systematic Combination of Projection and Ranking in Multi-Attribute Data Exploration",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09903343/1GZooOkjYzK",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09930144",
"title": "Out of the Plane: Flower Vs. Star Glyphs to Support High-Dimensional Exploration in Two-Dimensional Embeddings",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09930144/1HMOX2J2VMY",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccvw/2019/5023/0/502300b783",
"title": "Triplet-Aware Scene Graph Embeddings",
"doi": null,
"abstractUrl": "/proceedings-article/iccvw/2019/502300b783/1i5mEq1Ubfy",
"parentPublication": {
"id": "proceedings/iccvw/2019/5023/0",
"title": "2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2022/05/09128033",
"title": "Interpretation of Structural Preservation in Low-Dimensional Embeddings",
"doi": null,
"abstractUrl": "/journal/tk/2022/05/09128033/1l3u8JV5SP6",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/08/09301222",
"title": "<italic>embComp</italic>: Visual Interactive Comparison of Vector Embeddings",
"doi": null,
"abstractUrl": "/journal/tg/2022/08/09301222/1pK0Opgn59m",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vis4dh/2020/9153/0/915300a007",
"title": "Bio-inspired Structure Identification in Language Embeddings",
"doi": null,
"abstractUrl": "/proceedings-article/vis4dh/2020/915300a007/1pZ0Xs0EEqk",
"parentPublication": {
"id": "proceedings/vis4dh/2020/9153/0",
"title": "2020 IEEE 5th Workshop on Visualization for the Digital Humanities (VIS4DH)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/big-data/2020/6251/0/09377769",
"title": "Towards Tabular Embeddings, Training the Relational Models",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2020/09377769/1s64KLHTXHi",
"parentPublication": {
"id": "proceedings/big-data/2020/6251/0",
"title": "2020 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552226",
"articleId": "1xicaXrIayI",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552206",
"articleId": "1xic9jxItoI",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBaLr248De",
"name": "ttg202201-09552929s1-supp2-3114870.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552929s1-supp2-3114870.pdf",
"extension": "pdf",
"size": "11.8 MB",
"__typename": "WebExtraType"
},
{
"id": "1zBaLB1ItA4",
"name": "ttg202201-09552929s1-supp1-3114870.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552929s1-supp1-3114870.mp4",
"extension": "mp4",
"size": "30.8 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xic9jxItoI",
"doi": "10.1109/TVCG.2021.3114833",
"abstract": "We propose Steadiness and Cohesiveness, two novel metrics to measure the inter-cluster reliability of multidimensional projection (MDP), specifically how well the inter-cluster structures are preserved between the original high-dimensional space and the low-dimensional projection space. Measuring inter-cluster reliability is crucial as it directly affects how well inter-cluster tasks (e.g., identifying cluster relationships in the original space from a projected view) can be conducted; however, despite the importance of inter-cluster tasks, we found that previous metrics, such as Trustworthiness and Continuity, fail to measure inter-cluster reliability. Our metrics consider two aspects of the inter-cluster reliability: Steadiness measures the extent to which clusters in the projected space form clusters in the original space, and Cohesiveness measures the opposite. They extract random clusters with arbitrary shapes and positions in one space and evaluate how much the clusters are stretched or dispersed in the other space. Furthermore, our metrics can quantify pointwise distortions, allowing for the visualization of inter-cluster reliability in a projection, which we call a reliability map. Through quantitative experiments, we verify that our metrics precisely capture the distortions that harm inter-cluster reliability while previous metrics have difficulty capturing the distortions. A case study also demonstrates that our metrics and the reliability map 1) support users in selecting the proper projection techniques or hyperparameters and 2) prevent misinterpretation while performing inter-cluster tasks, thus allow an adequate identification of inter-cluster structure.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We propose Steadiness and Cohesiveness, two novel metrics to measure the inter-cluster reliability of multidimensional projection (MDP), specifically how well the inter-cluster structures are preserved between the original high-dimensional space and the low-dimensional projection space. Measuring inter-cluster reliability is crucial as it directly affects how well inter-cluster tasks (e.g., identifying cluster relationships in the original space from a projected view) can be conducted; however, despite the importance of inter-cluster tasks, we found that previous metrics, such as Trustworthiness and Continuity, fail to measure inter-cluster reliability. Our metrics consider two aspects of the inter-cluster reliability: Steadiness measures the extent to which clusters in the projected space form clusters in the original space, and Cohesiveness measures the opposite. They extract random clusters with arbitrary shapes and positions in one space and evaluate how much the clusters are stretched or dispersed in the other space. Furthermore, our metrics can quantify pointwise distortions, allowing for the visualization of inter-cluster reliability in a projection, which we call a reliability map. Through quantitative experiments, we verify that our metrics precisely capture the distortions that harm inter-cluster reliability while previous metrics have difficulty capturing the distortions. A case study also demonstrates that our metrics and the reliability map 1) support users in selecting the proper projection techniques or hyperparameters and 2) prevent misinterpretation while performing inter-cluster tasks, thus allow an adequate identification of inter-cluster structure.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We propose Steadiness and Cohesiveness, two novel metrics to measure the inter-cluster reliability of multidimensional projection (MDP), specifically how well the inter-cluster structures are preserved between the original high-dimensional space and the low-dimensional projection space. Measuring inter-cluster reliability is crucial as it directly affects how well inter-cluster tasks (e.g., identifying cluster relationships in the original space from a projected view) can be conducted; however, despite the importance of inter-cluster tasks, we found that previous metrics, such as Trustworthiness and Continuity, fail to measure inter-cluster reliability. Our metrics consider two aspects of the inter-cluster reliability: Steadiness measures the extent to which clusters in the projected space form clusters in the original space, and Cohesiveness measures the opposite. They extract random clusters with arbitrary shapes and positions in one space and evaluate how much the clusters are stretched or dispersed in the other space. Furthermore, our metrics can quantify pointwise distortions, allowing for the visualization of inter-cluster reliability in a projection, which we call a reliability map. Through quantitative experiments, we verify that our metrics precisely capture the distortions that harm inter-cluster reliability while previous metrics have difficulty capturing the distortions. A case study also demonstrates that our metrics and the reliability map 1) support users in selecting the proper projection techniques or hyperparameters and 2) prevent misinterpretation while performing inter-cluster tasks, thus allow an adequate identification of inter-cluster structure.",
"title": "Measuring and Explaining the Inter-Cluster Reliability of Multidimensional Projections",
"normalizedTitle": "Measuring and Explaining the Inter-Cluster Reliability of Multidimensional Projections",
"fno": "09552206",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Distortion",
"Reliability",
"Measurement",
"Distortion Measurement",
"Task Analysis",
"Data Visualization",
"Extraterrestrial Measurements",
"Multidimensional Projections",
"MDP Distortions",
"Inter Cluster Tasks",
"Inter Cluster Reliability",
"Distortion Metrics"
],
"authors": [
{
"givenName": "Hyeon",
"surname": "Jeon",
"fullName": "Hyeon Jeon",
"affiliation": "Seoul National University, South Korea",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Hyung-Kwon",
"surname": "Ko",
"fullName": "Hyung-Kwon Ko",
"affiliation": "Seoul National University, South Korea",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jaemin",
"surname": "Jo",
"fullName": "Jaemin Jo",
"affiliation": "Sungkyunkwan University, South Korea",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Youngtaek",
"surname": "Kim",
"fullName": "Youngtaek Kim",
"affiliation": "Seoul National University, South Korea",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jinwook",
"surname": "Seo",
"fullName": "Jinwook Seo",
"affiliation": "Seoul National University, South Korea",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "551-561",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/issre/1991/2143/0/00145346",
"title": "The use of software complexity metrics in software reliability modeling",
"doi": null,
"abstractUrl": "/proceedings-article/issre/1991/00145346/12OmNBgQFNh",
"parentPublication": {
"id": "proceedings/issre/1991/2143/0",
"title": "Proceedings. 1991 International Symposium on Software Reliability Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/issre/1992/2975/0/00285897",
"title": "Software quality metrics in space systems",
"doi": null,
"abstractUrl": "/proceedings-article/issre/1992/00285897/12OmNqJq4hg",
"parentPublication": {
"id": "proceedings/issre/1992/2975/0",
"title": "Proceedings Third International Symposium on Software Reliability Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hpcc-icess/2010/4214/0/4214a573",
"title": "A Trade-Off Between Reliability and Energy Efficiency for Inter-cluster Communication in Wireless Sensor Networks",
"doi": null,
"abstractUrl": "/proceedings-article/hpcc-icess/2010/4214a573/12OmNrYCY06",
"parentPublication": {
"id": "proceedings/hpcc-icess/2010/4214/0",
"title": "High Performance Computing and Communication & IEEE International Conference on Embedded Software and Systems, IEEE International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icassp/2004/8484/1/01326030",
"title": "Predicting foreground SH, SL and BNH DAM scores for multidimensional objective measure of speech quality",
"doi": null,
"abstractUrl": "/proceedings-article/icassp/2004/01326030/12OmNro0I2c",
"parentPublication": {
"id": "proceedings/icassp/2004/8484/1",
"title": "2004 IEEE International Conference on Acoustics, Speech, and Signal Processing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2015/7568/0/7568a133",
"title": "Simplified Stress and Simplified Silhouette Coefficient to a Faster Quality Evaluation of Multidimensional Projection Techniques and Feature Spaces",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2015/7568a133/12OmNscOUa1",
"parentPublication": {
"id": "proceedings/iv/2015/7568/0",
"title": "2015 19th International Conference on Information Visualisation (iV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/1990/2062/1/00118202",
"title": "Measuring image structures using a multiscale orientation field",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/1990/00118202/12OmNvjgWA4",
"parentPublication": {
"id": "proceedings/icpr/1990/2062/1",
"title": "Proceedings 10th International Conference on Pattern Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ats/2016/3809/0/3809a240",
"title": "Modeling Residual Lifetime of an IC Considering Spatial and Inter-Temporal Temperature Variations",
"doi": null,
"abstractUrl": "/proceedings-article/ats/2016/3809a240/12OmNzA6GKq",
"parentPublication": {
"id": "proceedings/ats/2016/3809/0",
"title": "2016 IEEE 25th Asian Test Symposium (ATS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacv/2022/0915/0/091500c763",
"title": "A Riemannian Framework for Analysis of Human Body Surface",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2022/091500c763/1B131rXOZDq",
"parentPublication": {
"id": "proceedings/wacv/2022/0915/0",
"title": "2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/12/09448469",
"title": "A Topological Similarity Measure Between Multi-Resolution Reeb Spaces",
"doi": null,
"abstractUrl": "/journal/tg/2022/12/09448469/1ugE7gaINC8",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2021/4509/0/450900i581",
"title": "Passive Inter-Photon Imaging",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2021/450900i581/1yeJuqwiGWs",
"parentPublication": {
"id": "proceedings/cvpr/2021/4509/0",
"title": "2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552929",
"articleId": "1xic3zJwVwI",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552224",
"articleId": "1xibZvRmYzm",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBb3VjZlKw",
"name": "ttg202201-09552206s1-supp2-3114833.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552206s1-supp2-3114833.pdf",
"extension": "pdf",
"size": "10.6 MB",
"__typename": "WebExtraType"
},
{
"id": "1zBb3kw615S",
"name": "ttg202201-09552206s1-supp1-3114833.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552206s1-supp1-3114833.mp4",
"extension": "mp4",
"size": "91.7 MB",
"__typename": "WebExtraType"
},
{
"id": "1zBb42t5bNe",
"name": "ttg202201-09552206s1-supp3-3114833.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552206s1-supp3-3114833.pdf",
"extension": "pdf",
"size": "4.52 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xibZvRmYzm",
"doi": "10.1109/TVCG.2021.3114769",
"abstract": "We present a differentiable volume rendering solution that provides differentiability of all continuous parameters of the volume rendering process. This differentiable renderer is used to steer the parameters towards a setting with an optimal solution of a problem-specific objective function. We have tailored the approach to volume rendering by enforcing a constant memory footprint via analytic inversion of the blending functions. This makes it independent of the number of sampling steps through the volume and facilitates the consideration of small-scale changes. The approach forms the basis for automatic optimizations regarding external parameters of the rendering process and the volumetric density field itself. We demonstrate its use for automatic viewpoint selection using differentiable entropy as objective, and for optimizing a transfer function from rendered images of a given volume. Optimization of per-voxel densities is addressed in two different ways: First, we mimic inverse tomography and optimize a 3D density field from images using an absorption model. This simplification enables comparisons with algebraic reconstruction techniques and state-of-the-art differentiable path tracers. Second, we introduce a novel approach for tomographic reconstruction from images using an emission-absorption model with post-shading via an arbitrary transfer function.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We present a differentiable volume rendering solution that provides differentiability of all continuous parameters of the volume rendering process. This differentiable renderer is used to steer the parameters towards a setting with an optimal solution of a problem-specific objective function. We have tailored the approach to volume rendering by enforcing a constant memory footprint via analytic inversion of the blending functions. This makes it independent of the number of sampling steps through the volume and facilitates the consideration of small-scale changes. The approach forms the basis for automatic optimizations regarding external parameters of the rendering process and the volumetric density field itself. We demonstrate its use for automatic viewpoint selection using differentiable entropy as objective, and for optimizing a transfer function from rendered images of a given volume. Optimization of per-voxel densities is addressed in two different ways: First, we mimic inverse tomography and optimize a 3D density field from images using an absorption model. This simplification enables comparisons with algebraic reconstruction techniques and state-of-the-art differentiable path tracers. Second, we introduce a novel approach for tomographic reconstruction from images using an emission-absorption model with post-shading via an arbitrary transfer function.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We present a differentiable volume rendering solution that provides differentiability of all continuous parameters of the volume rendering process. This differentiable renderer is used to steer the parameters towards a setting with an optimal solution of a problem-specific objective function. We have tailored the approach to volume rendering by enforcing a constant memory footprint via analytic inversion of the blending functions. This makes it independent of the number of sampling steps through the volume and facilitates the consideration of small-scale changes. The approach forms the basis for automatic optimizations regarding external parameters of the rendering process and the volumetric density field itself. We demonstrate its use for automatic viewpoint selection using differentiable entropy as objective, and for optimizing a transfer function from rendered images of a given volume. Optimization of per-voxel densities is addressed in two different ways: First, we mimic inverse tomography and optimize a 3D density field from images using an absorption model. This simplification enables comparisons with algebraic reconstruction techniques and state-of-the-art differentiable path tracers. Second, we introduce a novel approach for tomographic reconstruction from images using an emission-absorption model with post-shading via an arbitrary transfer function.",
"title": "Differentiable Direct Volume Rendering",
"normalizedTitle": "Differentiable Direct Volume Rendering",
"fno": "09552224",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Entropy",
"Image Reconstruction",
"Ray Tracing",
"Rendering Computer Graphics",
"Transfer Functions",
"Automatic Optimizations",
"External Parameters",
"Volumetric Density Field",
"Automatic Viewpoint Selection",
"Differentiable Entropy",
"Rendered Images",
"Given Volume",
"3 D Density Field",
"Algebraic Reconstruction Techniques",
"State Of The Art Differentiable Path Tracers",
"Arbitrary Transfer Function",
"Differentiable Direct Volume Rendering",
"Differentiable Volume Rendering Solution",
"Differentiability",
"Continuous Parameters",
"Volume Rendering Process",
"Differentiable Renderer",
"Optimal Solution",
"Problem Specific Objective Function",
"Constant Memory Footprint",
"Analytic Inversion",
"Blending Functions",
"Rendering Computer Graphics",
"Optimization",
"Image Reconstruction",
"Transfer Functions",
"Solid Modeling",
"Tomography",
"Image Color Analysis",
"Differentiable Rendering",
"Direct Volume Rendering",
"Automatic Differentiation"
],
"authors": [
{
"givenName": "Sebastian",
"surname": "Weiss",
"fullName": "Sebastian Weiss",
"affiliation": "Technical University of Munich, Germany",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Rüdiger",
"surname": "Westermann",
"fullName": "Rüdiger Westermann",
"affiliation": "Technical University of Munich, Germany",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "562-572",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/visual/1990/2083/0/00146362",
"title": "A procedural interface for volume rendering",
"doi": null,
"abstractUrl": "/proceedings-article/visual/1990/00146362/12OmNApLGMS",
"parentPublication": {
"id": "proceedings/visual/1990/2083/0",
"title": "1990 First IEEE Conference on Visualization",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cgi/2003/1946/0/19460002",
"title": "Hardware Assisted Multichannel Volume Rendering",
"doi": null,
"abstractUrl": "/proceedings-article/cgi/2003/19460002/12OmNCdk2xM",
"parentPublication": {
"id": "proceedings/cgi/2003/1946/0",
"title": "Computer Graphics International Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ieee-vis/2005/2766/0/01532808",
"title": "Scale-invariant volume rendering",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-vis/2005/01532808/12OmNyoAA5X",
"parentPublication": {
"id": "proceedings/ieee-vis/2005/2766/0",
"title": "Visualization Conference, IEEE",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2009/06/ttg2009061283",
"title": "Perception-Based Transparency Optimization for Direct Volume Rendering",
"doi": null,
"abstractUrl": "/journal/tg/2009/06/ttg2009061283/13rRUwIF69f",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2013/03/ttg2013030446",
"title": "Perceptually-Based Depth-Ordering Enhancement for Direct Volume Rendering",
"doi": null,
"abstractUrl": "/journal/tg/2013/03/ttg2013030446/13rRUwInvyw",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2001/03/v0253",
"title": "Volume Illustration: Nonphotorealistic Rendering of Volume Models",
"doi": null,
"abstractUrl": "/journal/tg/2001/03/v0253/13rRUxbTMyH",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2010/04/ttg2010040548",
"title": "Local Ambient Occlusion in Direct Volume Rendering",
"doi": null,
"abstractUrl": "/journal/tg/2010/04/ttg2010040548/13rRUy0HYRk",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/04/08316963",
"title": "A Generative Model for Volume Rendering",
"doi": null,
"abstractUrl": "/journal/tg/2019/04/08316963/181W9oUhqP9",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2021/2812/0/281200g068",
"title": "Differentiable Surface Rendering via Non-Differentiable Sampling",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/281200g068/1BmFpmQFMKA",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/02/09222562",
"title": "Homomorphic-Encrypted Volume Rendering",
"doi": null,
"abstractUrl": "/journal/tg/2021/02/09222562/1nTqvh6tnr2",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552206",
"articleId": "1xic9jxItoI",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552900",
"articleId": "1xic6f4Sc6I",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBayyrCS1G",
"name": "ttg202201-09552224s1-supp1-3114769.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552224s1-supp1-3114769.mp4",
"extension": "mp4",
"size": "31 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xic6f4Sc6I",
"doi": "10.1109/TVCG.2021.3114788",
"abstract": "Achieving high rendering quality in the visualization of large particle data, for example from large-scale molecular dynamics simulations, requires a significant amount of sub-pixel super-sampling, due to very high numbers of particles per pixel. Although it is impossible to super-sample all particles of large-scale data at interactive rates, efficient occlusion culling can decouple the overall data size from a high effective sampling rate of visible particles. However, while the latter is essential for domain scientists to be able to see important data features, performing occlusion culling by sampling or sorting the data is usually slow or error-prone due to visibility estimates of insufficient quality. We present a novel probabilistic culling architecture for super-sampled high-quality rendering of large particle data. Occlusion is dynamically determined at the sub-pixel level, without explicit visibility sorting or data simplification. We introduce confidence maps to probabilistically estimate confidence in the visibility data gathered so far. This enables progressive, confidence-based culling, helping to avoid wrong visibility decisions. In this way, we determine particle visibility with high accuracy, although only a small part of the data set is sampled. This enables extensive super-sampling of (partially) visible particles for high rendering quality, at a fraction of the cost of sampling all particles. For real-time performance with millions of particles, we exploit novel features of recent GPU architectures to group particles into two hierarchy levels, combining fine-grained culling with high frame rates.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Achieving high rendering quality in the visualization of large particle data, for example from large-scale molecular dynamics simulations, requires a significant amount of sub-pixel super-sampling, due to very high numbers of particles per pixel. Although it is impossible to super-sample all particles of large-scale data at interactive rates, efficient occlusion culling can decouple the overall data size from a high effective sampling rate of visible particles. However, while the latter is essential for domain scientists to be able to see important data features, performing occlusion culling by sampling or sorting the data is usually slow or error-prone due to visibility estimates of insufficient quality. We present a novel probabilistic culling architecture for super-sampled high-quality rendering of large particle data. Occlusion is dynamically determined at the sub-pixel level, without explicit visibility sorting or data simplification. We introduce confidence maps to probabilistically estimate confidence in the visibility data gathered so far. This enables progressive, confidence-based culling, helping to avoid wrong visibility decisions. In this way, we determine particle visibility with high accuracy, although only a small part of the data set is sampled. This enables extensive super-sampling of (partially) visible particles for high rendering quality, at a fraction of the cost of sampling all particles. For real-time performance with millions of particles, we exploit novel features of recent GPU architectures to group particles into two hierarchy levels, combining fine-grained culling with high frame rates.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Achieving high rendering quality in the visualization of large particle data, for example from large-scale molecular dynamics simulations, requires a significant amount of sub-pixel super-sampling, due to very high numbers of particles per pixel. Although it is impossible to super-sample all particles of large-scale data at interactive rates, efficient occlusion culling can decouple the overall data size from a high effective sampling rate of visible particles. However, while the latter is essential for domain scientists to be able to see important data features, performing occlusion culling by sampling or sorting the data is usually slow or error-prone due to visibility estimates of insufficient quality. We present a novel probabilistic culling architecture for super-sampled high-quality rendering of large particle data. Occlusion is dynamically determined at the sub-pixel level, without explicit visibility sorting or data simplification. We introduce confidence maps to probabilistically estimate confidence in the visibility data gathered so far. This enables progressive, confidence-based culling, helping to avoid wrong visibility decisions. In this way, we determine particle visibility with high accuracy, although only a small part of the data set is sampled. This enables extensive super-sampling of (partially) visible particles for high rendering quality, at a fraction of the cost of sampling all particles. For real-time performance with millions of particles, we exploit novel features of recent GPU architectures to group particles into two hierarchy levels, combining fine-grained culling with high frame rates.",
"title": "Probabilistic Occlusion Culling using Confidence Maps for High-Quality Rendering of Large Particle Data",
"normalizedTitle": "Probabilistic Occlusion Culling using Confidence Maps for High-Quality Rendering of Large Particle Data",
"fno": "09552900",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Probabilistic Logic",
"Rendering Computer Graphics",
"Data Visualization",
"Graphics Processing Units",
"Costs",
"Standards",
"Density Functional Theory",
"Large Scale Particle Data",
"Sub Pixel Occlusion Culling",
"Super Sampling",
"Anti Aliasing",
"Coverage",
"Probabilistic Methods"
],
"authors": [
{
"givenName": "Mohamed",
"surname": "Ibrahim",
"fullName": "Mohamed Ibrahim",
"affiliation": "King Abdullah University of Science and Technology (KAUST), Visual Computing Center, Thuwal, Saudi Arabia",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Peter",
"surname": "Rautek",
"fullName": "Peter Rautek",
"affiliation": "King Abdullah University of Science and Technology (KAUST), Visual Computing Center, Thuwal, Saudi Arabia",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Guido",
"surname": "Reina",
"fullName": "Guido Reina",
"affiliation": "Visualization Research Center (VISUS), University of Stuttgart, Germany",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Marco",
"surname": "Agus",
"fullName": "Marco Agus",
"affiliation": "College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Markus",
"surname": "Hadwiger",
"fullName": "Markus Hadwiger",
"affiliation": "King Abdullah University of Science and Technology (KAUST), Visual Computing Center, Thuwal, Saudi Arabia",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "573-582",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/ieee-vis/2004/8788/0/87880147",
"title": "Visibility Culling for Time-Varying Volume Rendering Using Temporal Occlusion Coherence",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-vis/2004/87880147/12OmNAY79mS",
"parentPublication": {
"id": "proceedings/ieee-vis/2004/8788/0",
"title": "Visualization Conference, IEEE",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ieee-vis/2002/7498/0/7498lloyd",
"title": "Horizon Occlusion Culling for Real-time Rendering of Hierarchical Terrains",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-vis/2002/7498lloyd/12OmNCxbXBX",
"parentPublication": {
"id": "proceedings/ieee-vis/2002/7498/0",
"title": "Visualization Conference, IEEE",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/csse/2008/3336/2/3336d058",
"title": "Efficient Occlusion Culling with Occupancy Proportion",
"doi": null,
"abstractUrl": "/proceedings-article/csse/2008/3336d058/12OmNvDZEXS",
"parentPublication": {
"id": "proceedings/csse/2008/3336/6",
"title": "Computer Science and Software Engineering, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ieee-vis/2003/2030/0/20300022",
"title": "Interactive View-Dependent Rendering with Conservative Occlusion Culling in Complex Environments",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-vis/2003/20300022/12OmNvvtGXd",
"parentPublication": {
"id": "proceedings/ieee-vis/2003/2030/0",
"title": "Visualization Conference, IEEE",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ieee-vis/2001/7200/0/7200elsana",
"title": "Integrating Occlusion Culling with View-Dependent Rendering",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-vis/2001/7200elsana/12OmNxbW4UY",
"parentPublication": {
"id": "proceedings/ieee-vis/2001/7200/0",
"title": "Visualization Conference, IEEE",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/biovis/2012/4729/0/06378589",
"title": "Towards real-time visualization of detailed neural tissue models: View frustum culling for parallel rendering",
"doi": null,
"abstractUrl": "/proceedings-article/biovis/2012/06378589/12OmNyRg4u5",
"parentPublication": {
"id": "proceedings/biovis/2012/4729/0",
"title": "2012 IEEE Symposium on Biological Data Visualization (BioVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pvg/2001/7223/0/72230067",
"title": "Parallel View-Dependent Isosurface Extraction Using Multi-Pass Occlusion Culling",
"doi": null,
"abstractUrl": "/proceedings-article/pvg/2001/72230067/12OmNynJMPK",
"parentPublication": {
"id": "proceedings/pvg/2001/7223/0",
"title": "Parallel and Large-Data Visualization and Graphics, IEEE Symposium on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cad-graphics/2013/2576/0/06814970",
"title": "Time and Space Coherent Occlusion Culling for Tileable Extended 3D Worlds",
"doi": null,
"abstractUrl": "/proceedings-article/cad-graphics/2013/06814970/12OmNzuIjnk",
"parentPublication": {
"id": "proceedings/cad-graphics/2013/2576/0",
"title": "2013 International Conference on Computer-Aided Design and Computer Graphics (CAD/Graphics)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tc/2006/08/t1024",
"title": "An Effective Visibility Culling Method Based on Cache Block",
"doi": null,
"abstractUrl": "/journal/tc/2006/08/t1024/13rRUIM2VB2",
"parentPublication": {
"id": "trans/tc",
"title": "IEEE Transactions on Computers",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2018/01/08017605",
"title": "Screen-Space Normal Distribution Function Caching for Consistent Multi-Resolution Rendering of Large Particle Data",
"doi": null,
"abstractUrl": "/journal/tg/2018/01/08017605/13rRUxly9dZ",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552224",
"articleId": "1xibZvRmYzm",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552891",
"articleId": "1xic5VPyxhu",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBaRJ5KQzS",
"name": "ttg202201-09552900s1-supp2-3114788.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552900s1-supp2-3114788.pdf",
"extension": "pdf",
"size": "64.9 MB",
"__typename": "WebExtraType"
},
{
"id": "1zBaSgczTgs",
"name": "ttg202201-09552900s1-supp1-3114788.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552900s1-supp1-3114788.mp4",
"extension": "mp4",
"size": "161 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xic5VPyxhu",
"doi": "10.1109/TVCG.2021.3114869",
"abstract": "In theory, efficient and high-quality rendering of unstructured data should greatly benefit from modern GPUs, but in practice, GPUs are often limited by the large amount of memory that large meshes require for element representation and for sample reconstruction acceleration structures. We describe a memory-optimized encoding for large unstructured meshes that efficiently encodes both the unstructured mesh and corresponding sample reconstruction acceleration structure, while still allowing for fast random-access sampling as required for rendering. We demonstrate that for large data our encoding allows for rendering even the 2.9 billion element Mars Lander on a single off-the-shelf GPU-and the largest 6.3 billion version on a pair of such GPUs.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In theory, efficient and high-quality rendering of unstructured data should greatly benefit from modern GPUs, but in practice, GPUs are often limited by the large amount of memory that large meshes require for element representation and for sample reconstruction acceleration structures. We describe a memory-optimized encoding for large unstructured meshes that efficiently encodes both the unstructured mesh and corresponding sample reconstruction acceleration structure, while still allowing for fast random-access sampling as required for rendering. We demonstrate that for large data our encoding allows for rendering even the 2.9 billion element Mars Lander on a single off-the-shelf GPU-and the largest 6.3 billion version on a pair of such GPUs.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In theory, efficient and high-quality rendering of unstructured data should greatly benefit from modern GPUs, but in practice, GPUs are often limited by the large amount of memory that large meshes require for element representation and for sample reconstruction acceleration structures. We describe a memory-optimized encoding for large unstructured meshes that efficiently encodes both the unstructured mesh and corresponding sample reconstruction acceleration structure, while still allowing for fast random-access sampling as required for rendering. We demonstrate that for large data our encoding allows for rendering even the 2.9 billion element Mars Lander on a single off-the-shelf GPU-and the largest 6.3 billion version on a pair of such GPUs.",
"title": "A Memory Efficient Encoding for Ray Tracing Large Unstructured Data",
"normalizedTitle": "A Memory Efficient Encoding for Ray Tracing Large Unstructured Data",
"fno": "09552891",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Rendering Computer Graphics",
"Memory Management",
"Encoding",
"Mars",
"NASA",
"Data Structures",
"Computational Modeling"
],
"authors": [
{
"givenName": "Ingo",
"surname": "Wald",
"fullName": "Ingo Wald",
"affiliation": "NVIDIA, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Nate",
"surname": "Morrical",
"fullName": "Nate Morrical",
"affiliation": "SCI Institute, University of Utah and NVIDIA, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Stefan",
"surname": "Zellmann",
"fullName": "Stefan Zellmann",
"affiliation": "University of Cologne, Chair of Computer Science, Germany",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "583-592",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/sibgrapi/2011/4548/0/4548a093",
"title": "Accurate Volume Rendering of Unstructured Hexahedral Meshes",
"doi": null,
"abstractUrl": "/proceedings-article/sibgrapi/2011/4548a093/12OmNCcbE5T",
"parentPublication": {
"id": "proceedings/sibgrapi/2011/4548/0",
"title": "2011 24th SIBGRAPI Conference on Graphics, Patterns and Images",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cgi/2003/1946/0/19460202",
"title": "Ray Tracing Height Fields",
"doi": null,
"abstractUrl": "/proceedings-article/cgi/2003/19460202/12OmNvrdI3r",
"parentPublication": {
"id": "proceedings/cgi/2003/1946/0",
"title": "Computer Graphics International Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ieee-vis/2004/8788/0/87880433",
"title": "TetSplat Real-Time Rendering and Volume Clipping of Large Unstructured Tetrahedral Meshes",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-vis/2004/87880433/12OmNzRHOOj",
"parentPublication": {
"id": "proceedings/ieee-vis/2004/8788/0",
"title": "Visualization Conference, IEEE",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pacific-graphics/2010/4205/0/4205a101",
"title": "GPU-Based Ray Tracing of Splats",
"doi": null,
"abstractUrl": "/proceedings-article/pacific-graphics/2010/4205a101/12OmNzwHvuo",
"parentPublication": {
"id": "proceedings/pacific-graphics/2010/4205/0",
"title": "Pacific Conference on Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2011/03/ttg2011030305",
"title": "A Comparison of Gradient Estimation Methods for Volume Rendering on Unstructured Meshes",
"doi": null,
"abstractUrl": "/journal/tg/2011/03/ttg2011030305/13rRUx0xPi5",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2005/03/v0285",
"title": "Hardware-Assisted Visibility Sorting for Unstructured Volume Rendering",
"doi": null,
"abstractUrl": "/journal/tg/2005/03/v0285/13rRUxOdD89",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09904457",
"title": "Quick Clusters: A GPU-Parallel Partitioning for Efficient Path Tracing of Unstructured Volumetric Grids",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09904457/1H1gpFOnUeQ",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vis/2019/4941/0/08933539",
"title": "Efficient Space Skipping and Adaptive Sampling of Unstructured Volumes Using Hardware Accelerated Ray Tracing",
"doi": null,
"abstractUrl": "/proceedings-article/vis/2019/08933539/1fTgIhNytI4",
"parentPublication": {
"id": "proceedings/vis/2019/4941/0",
"title": "2019 IEEE Visualization Conference (VIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ldav/2020/8468/0/846800a042",
"title": "Spatial Partitioning Strategies for Memory-Efficient Ray Tracing of Particles",
"doi": null,
"abstractUrl": "/proceedings-article/ldav/2020/846800a042/1pZ0TM9iMHm",
"parentPublication": {
"id": "proceedings/ldav/2020/8468/0",
"title": "2020 IEEE 10th Symposium on Large Data Analysis and Visualization (LDAV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/08/09286513",
"title": "Accelerating Unstructured Mesh Point Location With RT Cores",
"doi": null,
"abstractUrl": "/journal/tg/2022/08/09286513/1porhlu0eEo",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552900",
"articleId": "1xic6f4Sc6I",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552916",
"articleId": "1xic8Hlfu4o",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xic8Hlfu4o",
"doi": "10.1109/TVCG.2021.3114880",
"abstract": "We present a pyramid-based scatterplot sampling technique to avoid overplotting and enable progressive and streaming visualization of large data. Our technique is based on a multiresolution pyramid-based decomposition of the underlying density map and makes use of the density values in the pyramid to guide the sampling at each scale for preserving the relative data densities and outliers. We show that our technique is competitive in quality with state-of-the-art methods and runs faster by about an order of magnitude. Also, we have adapted it to deliver progressive and streaming data visualization by processing the data in chunks and updating the scatterplot areas with visible changes in the density map. A quantitative evaluation shows that our approach generates stable and faithful progressive samples that are comparable to the state-of-the-art method in preserving relative densities and superior to it in keeping outliers and stability when switching frames. We present two case studies that demonstrate the effectiveness of our approach for exploring large data.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We present a pyramid-based scatterplot sampling technique to avoid overplotting and enable progressive and streaming visualization of large data. Our technique is based on a multiresolution pyramid-based decomposition of the underlying density map and makes use of the density values in the pyramid to guide the sampling at each scale for preserving the relative data densities and outliers. We show that our technique is competitive in quality with state-of-the-art methods and runs faster by about an order of magnitude. Also, we have adapted it to deliver progressive and streaming data visualization by processing the data in chunks and updating the scatterplot areas with visible changes in the density map. A quantitative evaluation shows that our approach generates stable and faithful progressive samples that are comparable to the state-of-the-art method in preserving relative densities and superior to it in keeping outliers and stability when switching frames. We present two case studies that demonstrate the effectiveness of our approach for exploring large data.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We present a pyramid-based scatterplot sampling technique to avoid overplotting and enable progressive and streaming visualization of large data. Our technique is based on a multiresolution pyramid-based decomposition of the underlying density map and makes use of the density values in the pyramid to guide the sampling at each scale for preserving the relative data densities and outliers. We show that our technique is competitive in quality with state-of-the-art methods and runs faster by about an order of magnitude. Also, we have adapted it to deliver progressive and streaming data visualization by processing the data in chunks and updating the scatterplot areas with visible changes in the density map. A quantitative evaluation shows that our approach generates stable and faithful progressive samples that are comparable to the state-of-the-art method in preserving relative densities and superior to it in keeping outliers and stability when switching frames. We present two case studies that demonstrate the effectiveness of our approach for exploring large data.",
"title": "Pyramid-based Scatterplots Sampling for Progressive and Streaming Data Visualization",
"normalizedTitle": "Pyramid-based Scatterplots Sampling for Progressive and Streaming Data Visualization",
"fno": "09552916",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Data Analysis",
"Data Visualisation",
"Image Resolution",
"Sampling Methods",
"Progressive Samples",
"Relative Densities",
"Pyramid Based Scatterplots Sampling",
"Streaming Data Visualization",
"Pyramid Based Scatterplot Sampling Technique",
"Streaming Visualization",
"Multiresolution Pyramid Based Decomposition",
"Underlying Density Map",
"Relative Data Densities",
"Scatterplot Areas",
"Data Visualization",
"Sampling Methods",
"Coherence",
"Reservoirs",
"Scalability",
"Visual Analytics",
"Rivers",
"Scatterplots",
"Sampling",
"Pyramid",
"Progressive Visualization",
"Streaming Visualization",
"Scalability",
"Big Data"
],
"authors": [
{
"givenName": "Xin",
"surname": "Chen",
"fullName": "Xin Chen",
"affiliation": "Shandong University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jian",
"surname": "Zhang",
"fullName": "Jian Zhang",
"affiliation": "CNIC, CAS, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Chi-Wing",
"surname": "Fu",
"fullName": "Chi-Wing Fu",
"affiliation": "Dept. of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jean-Daniel",
"surname": "Fekete",
"fullName": "Jean-Daniel Fekete",
"affiliation": "University Paris-Saclay, CNRS, Inria, LISN, France",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yunhai",
"surname": "Wang",
"fullName": "Yunhai Wang",
"affiliation": "Shandong University, China",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "593-603",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/wsc/2002/7614/2/01166424",
"title": "Importance sampling for multimodal functions and application to pricing exotic options",
"doi": null,
"abstractUrl": "/proceedings-article/wsc/2002/01166424/12OmNBIFmvx",
"parentPublication": {
"id": "proceedings/wsc/2002/7614/2",
"title": "Proceedings of the 2002 Winter Simulation Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icip/1998/8821/2/882120747",
"title": "An adaptive irregular sampling method for progressive transmission",
"doi": null,
"abstractUrl": "/proceedings-article/icip/1998/882120747/12OmNqJ8tbK",
"parentPublication": {
"id": "proceedings/icip/1998/8821/3",
"title": "Image Processing, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fskd/2008/3305/4/3305d081",
"title": "Motion Determination Using Non-uniform Sampling Based Density Clustering",
"doi": null,
"abstractUrl": "/proceedings-article/fskd/2008/3305d081/12OmNxFJXu2",
"parentPublication": {
"id": "proceedings/fskd/2008/3305/4",
"title": "Fuzzy Systems and Knowledge Discovery, Fourth International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccee/2009/3925/1/3925a610",
"title": "Developing Novel and Effective Approach for Association Rule Mining Using Progressive Sampling",
"doi": null,
"abstractUrl": "/proceedings-article/iccee/2009/3925a610/12OmNyUFfXz",
"parentPublication": {
"id": "iccee/2009/3925/1",
"title": "Computer and Electrical Engineering, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/1994/6275/0/00577129",
"title": "The farthest point strategy for progressive image sampling",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/1994/00577129/12OmNyugyHO",
"parentPublication": {
"id": "proceedings/icpr/1994/6275/0",
"title": "12th IAPR International Conference on Pattern Recognition, 1994",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2017/07/07473883",
"title": "Approximated and User Steerable tSNE for Progressive Visual Analytics",
"doi": null,
"abstractUrl": "/journal/tg/2017/07/07473883/13rRUxly8T1",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2020/02/08462793",
"title": "PANENE: A Progressive Algorithm for Indexing and Querying Approximate <italic>k</italic>-Nearest Neighbors",
"doi": null,
"abstractUrl": "/journal/tg/2020/02/08462793/13w3lozFWqB",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2020/01/08807244",
"title": "Data Sampling in Multi-view and Multi-class Scatterplots via Set Cover Optimization",
"doi": null,
"abstractUrl": "/journal/tg/2020/01/08807244/1cG6natfOKY",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2020/01/08809844",
"title": "A Recursive Subdivision Technique for Sampling Multi-class Scatterplots",
"doi": null,
"abstractUrl": "/journal/tg/2020/01/08809844/1cHEfHRrSOQ",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/02/09226404",
"title": "Evaluation of Sampling Methods for Scatterplots",
"doi": null,
"abstractUrl": "/journal/tg/2021/02/09226404/1nYqk0TjyeY",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552891",
"articleId": "1xic5VPyxhu",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552249",
"articleId": "1xicaqbwmA0",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBb0kD6BSo",
"name": "ttg202201-09552916s1-tvcg-3114880-mm.zip",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552916s1-tvcg-3114880-mm.zip",
"extension": "zip",
"size": "7.72 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xicaqbwmA0",
"doi": "10.1109/TVCG.2021.3114854",
"abstract": "Labels, short textual annotations are an important component of data visualizations, illustrations, infographics, and geographical maps. In interactive applications, the labeling method responsible for positioning the labels should not take the resources from the application itself. In other words, the labeling method should provide the result as fast as possible. In this work, we propose a greedy point-feature labeling method running on GPU. In contrast to existing methods that position the labels sequentially, the proposed method positions several labels in parallel. Yet, we guarantee that the positioned labels will not overlap, nor will they overlap important visual features. When the proposed method is searching for the label position of a point-feature, the available label candidates are evaluated with respect to overlaps with important visual features, conflicts with label candidates of other point-features, and their ambiguity. The evaluation of each label candidate is done in constant time independently from the number of point-features, the number of important visual features, and the resolution of the created image. Our measurements indicate that the proposed method is able to position more labels than existing greedy methods that do not evaluate conflicts between the label candidates. At the same time, the proposed method achieves a significant increase in performance. The increase in performance is mainly due to the parallelization and the efficient evaluation of label candidates.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Labels, short textual annotations are an important component of data visualizations, illustrations, infographics, and geographical maps. In interactive applications, the labeling method responsible for positioning the labels should not take the resources from the application itself. In other words, the labeling method should provide the result as fast as possible. In this work, we propose a greedy point-feature labeling method running on GPU. In contrast to existing methods that position the labels sequentially, the proposed method positions several labels in parallel. Yet, we guarantee that the positioned labels will not overlap, nor will they overlap important visual features. When the proposed method is searching for the label position of a point-feature, the available label candidates are evaluated with respect to overlaps with important visual features, conflicts with label candidates of other point-features, and their ambiguity. The evaluation of each label candidate is done in constant time independently from the number of point-features, the number of important visual features, and the resolution of the created image. Our measurements indicate that the proposed method is able to position more labels than existing greedy methods that do not evaluate conflicts between the label candidates. At the same time, the proposed method achieves a significant increase in performance. The increase in performance is mainly due to the parallelization and the efficient evaluation of label candidates.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Labels, short textual annotations are an important component of data visualizations, illustrations, infographics, and geographical maps. In interactive applications, the labeling method responsible for positioning the labels should not take the resources from the application itself. In other words, the labeling method should provide the result as fast as possible. In this work, we propose a greedy point-feature labeling method running on GPU. In contrast to existing methods that position the labels sequentially, the proposed method positions several labels in parallel. Yet, we guarantee that the positioned labels will not overlap, nor will they overlap important visual features. When the proposed method is searching for the label position of a point-feature, the available label candidates are evaluated with respect to overlaps with important visual features, conflicts with label candidates of other point-features, and their ambiguity. The evaluation of each label candidate is done in constant time independently from the number of point-features, the number of important visual features, and the resolution of the created image. Our measurements indicate that the proposed method is able to position more labels than existing greedy methods that do not evaluate conflicts between the label candidates. At the same time, the proposed method achieves a significant increase in performance. The increase in performance is mainly due to the parallelization and the efficient evaluation of label candidates.",
"title": "Rapid Labels: Point-Feature Labeling on GPU",
"normalizedTitle": "Rapid Labels: Point-Feature Labeling on GPU",
"fno": "09552249",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Labeling",
"Visualization",
"Layout",
"Data Visualization",
"Graphics Processing Units",
"Annotations",
"Optimization",
"Label Placement",
"Point Feature Labeling",
"GPU"
],
"authors": [
{
"givenName": "Vaclav",
"surname": "Pavlovec",
"fullName": "Vaclav Pavlovec",
"affiliation": "Faculty of Electrical Engineering, Czech Technical University in Prague, Czech Republic",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Ladislav",
"surname": "Cmolik",
"fullName": "Ladislav Cmolik",
"affiliation": "Faculty of Electrical Engineering, Czech Technical University in Prague, Czech Republic",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "604-613",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/pacificvis/2017/5738/0/08031608",
"title": "Radial contour labeling with straight leaders",
"doi": null,
"abstractUrl": "/proceedings-article/pacificvis/2017/08031608/12OmNAKuoSv",
"parentPublication": {
"id": "proceedings/pacificvis/2017/5738/0",
"title": "2017 IEEE Pacific Visualization Symposium (PacificVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/apvis/2007/0808/0/04126220",
"title": "Many-to-one boundary labeling",
"doi": null,
"abstractUrl": "/proceedings-article/apvis/2007/04126220/12OmNBlFR2L",
"parentPublication": {
"id": "proceedings/apvis/2007/0808/0",
"title": "Asia-Pacific Symposium on Visualisation 2007",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pacificvis/2010/6685/0/05429592",
"title": "Crossing-free many-to-one boundary labeling with hyperleaders",
"doi": null,
"abstractUrl": "/proceedings-article/pacificvis/2010/05429592/12OmNyqzM3q",
"parentPublication": {
"id": "proceedings/pacificvis/2010/6685/0",
"title": "2010 IEEE Pacific Visualization Symposium (PacificVis 2010)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2008/06/ttg2008061237",
"title": "Particle-based labeling: Fast point-feature labeling without obscuring other visual features",
"doi": null,
"abstractUrl": "/journal/tg/2008/06/ttg2008061237/13rRUwbaqUM",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/01/08440077",
"title": "Labels on Levels: Labeling of Multi-Scale Multi-Instance and Crowded 3D Biological Environments",
"doi": null,
"abstractUrl": "/journal/tg/2019/01/08440077/17D45XH89nI",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/04/09207965",
"title": "Mixed Labeling: Integrating Internal and External Labels",
"doi": null,
"abstractUrl": "/journal/tg/2022/04/09207965/1nuwBNaxzjy",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aivr/2020/7463/0/746300a099",
"title": "Shooting Labels: 3D Semantic Labeling by Virtual Reality",
"doi": null,
"abstractUrl": "/proceedings-article/aivr/2020/746300a099/1qpzznqhVHW",
"parentPublication": {
"id": "proceedings/aivr/2020/7463/0",
"title": "2020 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/2021/04/09437800",
"title": "Collaborative VR-Based 3D Labeling of Live-Captured Scenes by Remote Users",
"doi": null,
"abstractUrl": "/magazine/cg/2021/04/09437800/1tL6FQbaHG8",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/11/09523830",
"title": "A Partially-Sorted Concentric Layout for Efficient Label Localization in Augmented Reality",
"doi": null,
"abstractUrl": "/journal/tg/2021/11/09523830/1wpqs1dtKes",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2021/4509/0/450900c340",
"title": "Re-labeling ImageNet: from Single to Multi-Labels, from Global to Localized Labels",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2021/450900c340/1yeJiMpCAcE",
"parentPublication": {
"id": "proceedings/cvpr/2021/4509/0",
"title": "2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552916",
"articleId": "1xic8Hlfu4o",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552856",
"articleId": "1xic3JUxdG8",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBb6rJxdyE",
"name": "ttg202201-09552249s1-supp2-3114854.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552249s1-supp2-3114854.pdf",
"extension": "pdf",
"size": "10.5 MB",
"__typename": "WebExtraType"
},
{
"id": "1zBb6SDsbRK",
"name": "ttg202201-09552249s1-supp1-3114854.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552249s1-supp1-3114854.mp4",
"extension": "mp4",
"size": "159 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xic3JUxdG8",
"doi": "10.1109/TVCG.2021.3114817",
"abstract": "t-distributed Stochastic Neighbour Embedding (t-SNE) has become a standard for exploratory data analysis, as it is capable of revealing clusters even in complex data while requiring minimal user input. While its run-time complexity limited it to small datasets in the past, recent efforts improved upon the expensive similarity computations and the previously quadratic minimization. Nevertheless, t-SNE still has high runtime and memory costs when operating on millions of points. We present a novel method for executing the t-SNE minimization. While our method overall retains a linear runtime complexity, we obtain a significant performance increase in the most expensive part of the minimization. We achieve a significant improvement without a noticeable decrease in accuracy even when targeting a 3D embedding. Our method constructs a pair of spatial hierarchies over the embedding, which are simultaneously traversed to approximate many N-body interactions at once. We demonstrate an efficient GPGPU implementation and evaluate its performance against state-of-the-art methods on a variety of datasets.",
"abstracts": [
{
"abstractType": "Regular",
"content": "t-distributed Stochastic Neighbour Embedding (t-SNE) has become a standard for exploratory data analysis, as it is capable of revealing clusters even in complex data while requiring minimal user input. While its run-time complexity limited it to small datasets in the past, recent efforts improved upon the expensive similarity computations and the previously quadratic minimization. Nevertheless, t-SNE still has high runtime and memory costs when operating on millions of points. We present a novel method for executing the t-SNE minimization. While our method overall retains a linear runtime complexity, we obtain a significant performance increase in the most expensive part of the minimization. We achieve a significant improvement without a noticeable decrease in accuracy even when targeting a 3D embedding. Our method constructs a pair of spatial hierarchies over the embedding, which are simultaneously traversed to approximate many N-body interactions at once. We demonstrate an efficient GPGPU implementation and evaluate its performance against state-of-the-art methods on a variety of datasets.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "t-distributed Stochastic Neighbour Embedding (t-SNE) has become a standard for exploratory data analysis, as it is capable of revealing clusters even in complex data while requiring minimal user input. While its run-time complexity limited it to small datasets in the past, recent efforts improved upon the expensive similarity computations and the previously quadratic minimization. Nevertheless, t-SNE still has high runtime and memory costs when operating on millions of points. We present a novel method for executing the t-SNE minimization. While our method overall retains a linear runtime complexity, we obtain a significant performance increase in the most expensive part of the minimization. We achieve a significant improvement without a noticeable decrease in accuracy even when targeting a 3D embedding. Our method constructs a pair of spatial hierarchies over the embedding, which are simultaneously traversed to approximate many N-body interactions at once. We demonstrate an efficient GPGPU implementation and evaluate its performance against state-of-the-art methods on a variety of datasets.",
"title": "An Efficient Dual-Hierarchy t-SNE Minimization",
"normalizedTitle": "An Efficient Dual-Hierarchy t-SNE Minimization",
"fno": "09552856",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Computational Complexity",
"Data Analysis",
"Sampling Methods",
"Stochastic Processes",
"Efficient Dual Hierarchy T SNE Minimization",
"Stochastic Neighbour Embedding",
"Exploratory Data Analysis",
"Complex Data",
"Minimal User Input",
"Run Time Complexity",
"Expensive Similarity Computations",
"Quadratic Minimization",
"High Runtime",
"Memory Costs",
"Linear Runtime Complexity",
"Significant Performance Increase",
"Expensive Part",
"Method Constructs",
"Spatial Hierarchies",
"Efficient GPGPU Implementation",
"Minimization",
"Runtime",
"Complexity Theory",
"Kernel",
"Three Dimensional Displays",
"Graphics Processing Units",
"Force",
"High Dimensional Data",
"Dimensionality Reduction",
"Parallel Data Structures",
"Dual Hierarchy",
"GPGPU"
],
"authors": [
{
"givenName": "Mark",
"surname": "van de Ruit",
"fullName": "Mark van de Ruit",
"affiliation": "Delft University of Technology, Netherlands",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Markus",
"surname": "Billeter",
"fullName": "Markus Billeter",
"affiliation": "University of Leeds, England",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Elmar",
"surname": "Eisemann",
"fullName": "Elmar Eisemann",
"affiliation": "Delft University of Technology, Netherlands",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "614-622",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/icdar/2017/3586/1/3586a487",
"title": "Nonlinear Manifold Embedding on Keyword Spotting Using t-SNE",
"doi": null,
"abstractUrl": "/proceedings-article/icdar/2017/3586a487/12OmNzlUKGo",
"parentPublication": {
"id": "proceedings/icdar/2017/3586/1",
"title": "2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sbac-pad/2018/7769/0/08645912",
"title": "T-SNE-CUDA: GPU-Accelerated T-SNE and its Applications to Modern Data",
"doi": null,
"abstractUrl": "/proceedings-article/sbac-pad/2018/08645912/17QjJeZi1UO",
"parentPublication": {
"id": "proceedings/sbac-pad/2018/7769/0",
"title": "2018 30th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iiai-aai/2018/7447/0/744701a390",
"title": "A New Way of Visualizing Curricula Using Competencies: Cosine Similarity and t-SNE",
"doi": null,
"abstractUrl": "/proceedings-article/iiai-aai/2018/744701a390/19m3BVKUOLm",
"parentPublication": {
"id": "proceedings/iiai-aai/2018/7447/0",
"title": "2018 7th International Congress on Advanced Applied Informatics (IIAI-AAI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/big-data/2022/8045/0/10020217",
"title": "Informative Initialization and Kernel Selection Improves t-SNE for Biological Sequences",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2022/10020217/1KfT8iuxRS0",
"parentPublication": {
"id": "proceedings/big-data/2022/8045/0",
"title": "2022 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2020/01/08811606",
"title": "GPGPU Linear Complexity t-SNE Optimization",
"doi": null,
"abstractUrl": "/journal/tg/2020/01/08811606/1cJj4SRFHeE",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2020/08/09064929",
"title": "t-viSNE: Interactive Assessment and Interpretation of t-SNE Projections",
"doi": null,
"abstractUrl": "/journal/tg/2020/08/09064929/1iZGzFjpwPu",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2021/8808/0/09412900",
"title": "q-SNE: Visualizing Data using q-Gaussian Distributed Stochastic Neighbor Embedding",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2021/09412900/1tmhROYroSA",
"parentPublication": {
"id": "proceedings/icpr/2021/8808/0",
"title": "2020 25th International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2021/9184/0/918400b691",
"title": "Fast Similarity Computation for t-SNE",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2021/918400b691/1uGXpqMZXag",
"parentPublication": {
"id": "proceedings/icde/2021/9184/0",
"title": "2021 IEEE 37th International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icisce/2020/6406/0/640600c274",
"title": "Wind Turbine Rolling Bearing Fault Diagnosis Using t-SNE and GWO-SVM",
"doi": null,
"abstractUrl": "/proceedings-article/icisce/2020/640600c274/1x3kI5MLOCs",
"parentPublication": {
"id": "proceedings/icisce/2020/6406/0",
"title": "2020 7th International Conference on Information Science and Control Engineering (ICISCE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/01/09552433",
"title": "Joint <italic>t</italic>-SNE for Comparable Projections of Multiple High-Dimensional Datasets",
"doi": null,
"abstractUrl": "/journal/tg/2022/01/09552433/1xic8QCTZRe",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552249",
"articleId": "1xicaqbwmA0",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552433",
"articleId": "1xic8QCTZRe",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBaM4x9cTS",
"name": "ttg202201-09552856s1-supp2-3114817.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552856s1-supp2-3114817.pdf",
"extension": "pdf",
"size": "44.1 MB",
"__typename": "WebExtraType"
},
{
"id": "1zBaMrymkUg",
"name": "ttg202201-09552856s1-supp1-3114817.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552856s1-supp1-3114817.mp4",
"extension": "mp4",
"size": "97.4 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xic8QCTZRe",
"doi": "10.1109/TVCG.2021.3114765",
"abstract": "We present Joint t-Stochastic Neighbor Embedding (Joint t-SNE), a technique to generate comparable projections of multiple high-dimensional datasets. Although t-SNE has been widely employed to visualize high-dimensional datasets from various domains, it is limited to projecting a single dataset. When a series of high-dimensional datasets, such as datasets changing over time, is projected independently using t-SNE, misaligned layouts are obtained. Even items with identical features across datasets are projected to different locations, making the technique unsuitable for comparison tasks. To tackle this problem, we introduce edge similarity, which captures the similarities between two adjacent time frames based on the Graphlet Frequency Distribution (GFD). We then integrate a novel loss term into the t-SNE loss function, which we call vector constraints, to preserve the vectors between projected points across the projections, allowing these points to serve as visual landmarks for direct comparisons between projections. Using synthetic datasets whose ground-truth structures are known, we show that Joint t-SNE outperforms existing techniques, including Dynamic t-SNE, in terms of local coherence error, Kullback-Leibler divergence, and neighborhood preservation. We also showcase a real-world use case to visualize and compare the activation of different layers of a neural network.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We present Joint t-Stochastic Neighbor Embedding (Joint t-SNE), a technique to generate comparable projections of multiple high-dimensional datasets. Although t-SNE has been widely employed to visualize high-dimensional datasets from various domains, it is limited to projecting a single dataset. When a series of high-dimensional datasets, such as datasets changing over time, is projected independently using t-SNE, misaligned layouts are obtained. Even items with identical features across datasets are projected to different locations, making the technique unsuitable for comparison tasks. To tackle this problem, we introduce edge similarity, which captures the similarities between two adjacent time frames based on the Graphlet Frequency Distribution (GFD). We then integrate a novel loss term into the t-SNE loss function, which we call vector constraints, to preserve the vectors between projected points across the projections, allowing these points to serve as visual landmarks for direct comparisons between projections. Using synthetic datasets whose ground-truth structures are known, we show that Joint t-SNE outperforms existing techniques, including Dynamic t-SNE, in terms of local coherence error, Kullback-Leibler divergence, and neighborhood preservation. We also showcase a real-world use case to visualize and compare the activation of different layers of a neural network.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We present Joint t-Stochastic Neighbor Embedding (Joint t-SNE), a technique to generate comparable projections of multiple high-dimensional datasets. Although t-SNE has been widely employed to visualize high-dimensional datasets from various domains, it is limited to projecting a single dataset. When a series of high-dimensional datasets, such as datasets changing over time, is projected independently using t-SNE, misaligned layouts are obtained. Even items with identical features across datasets are projected to different locations, making the technique unsuitable for comparison tasks. To tackle this problem, we introduce edge similarity, which captures the similarities between two adjacent time frames based on the Graphlet Frequency Distribution (GFD). We then integrate a novel loss term into the t-SNE loss function, which we call vector constraints, to preserve the vectors between projected points across the projections, allowing these points to serve as visual landmarks for direct comparisons between projections. Using synthetic datasets whose ground-truth structures are known, we show that Joint t-SNE outperforms existing techniques, including Dynamic t-SNE, in terms of local coherence error, Kullback-Leibler divergence, and neighborhood preservation. We also showcase a real-world use case to visualize and compare the activation of different layers of a neural network.",
"title": "Joint <italic>t</italic>-SNE for Comparable Projections of Multiple High-Dimensional Datasets",
"normalizedTitle": "Joint t-SNE for Comparable Projections of Multiple High-Dimensional Datasets",
"fno": "09552433",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Visualization",
"Task Analysis",
"Optimization",
"Time Measurement",
"Position Measurement",
"Gain Measurement",
"Distortion",
"High Dimensional Data",
"Projection",
"Embedding",
"T Stochastic Neighbor Embedding"
],
"authors": [
{
"givenName": "Yinqiao",
"surname": "Wang",
"fullName": "Yinqiao Wang",
"affiliation": "Shandong University, CN, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Lu",
"surname": "Chen",
"fullName": "Lu Chen",
"affiliation": "Shandong University, CN, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jaemin",
"surname": "Jo",
"fullName": "Jaemin Jo",
"affiliation": "Sungkyunkwan University, KR, South Korea",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yunhai",
"surname": "Wang",
"fullName": "Yunhai Wang",
"affiliation": "Shandong University, CN, China",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "623-632",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/icdar/2017/3586/1/3586a487",
"title": "Nonlinear Manifold Embedding on Keyword Spotting Using t-SNE",
"doi": null,
"abstractUrl": "/proceedings-article/icdar/2017/3586a487/12OmNzlUKGo",
"parentPublication": {
"id": "proceedings/icdar/2017/3586/1",
"title": "2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/greencom-ithingscpscom/2013/5046/0/06682333",
"title": "Facial Expression Recognition Based on t-SNE and AdaboostM2",
"doi": null,
"abstractUrl": "/proceedings-article/greencom-ithingscpscom/2013/06682333/12OmNzmclTi",
"parentPublication": {
"id": "proceedings/greencom-ithingscpscom/2013/5046/0",
"title": "2013 IEEE International Conference on Green Computing and Communications (GreenCom) and IEEE Internet of Things(iThings) and IEEE Cyber, Physical and Social Computing(CPSCom)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sbac-pad/2018/7769/0/08645912",
"title": "T-SNE-CUDA: GPU-Accelerated T-SNE and its Applications to Modern Data",
"doi": null,
"abstractUrl": "/proceedings-article/sbac-pad/2018/08645912/17QjJeZi1UO",
"parentPublication": {
"id": "proceedings/sbac-pad/2018/7769/0",
"title": "2018 30th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/big-data/2022/8045/0/10020217",
"title": "Informative Initialization and Kernel Selection Improves t-SNE for Biological Sequences",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2022/10020217/1KfT8iuxRS0",
"parentPublication": {
"id": "proceedings/big-data/2022/8045/0",
"title": "2022 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2020/01/08811606",
"title": "GPGPU Linear Complexity t-SNE Optimization",
"doi": null,
"abstractUrl": "/journal/tg/2020/01/08811606/1cJj4SRFHeE",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2020/08/09064929",
"title": "t-viSNE: Interactive Assessment and Interpretation of t-SNE Projections",
"doi": null,
"abstractUrl": "/journal/tg/2020/08/09064929/1iZGzFjpwPu",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ssiai/2020/5745/0/09094599",
"title": "Visualization and Detection of Changes in Brain States Using t-SNE",
"doi": null,
"abstractUrl": "/proceedings-article/ssiai/2020/09094599/1jVQEe9O2vS",
"parentPublication": {
"id": "proceedings/ssiai/2020/5745/0",
"title": "2020 IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2021/8808/0/09412900",
"title": "q-SNE: Visualizing Data using q-Gaussian Distributed Stochastic Neighbor Embedding",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2021/09412900/1tmhROYroSA",
"parentPublication": {
"id": "proceedings/icpr/2021/8808/0",
"title": "2020 25th International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icisce/2020/6406/0/640600c274",
"title": "Wind Turbine Rolling Bearing Fault Diagnosis Using t-SNE and GWO-SVM",
"doi": null,
"abstractUrl": "/proceedings-article/icisce/2020/640600c274/1x3kI5MLOCs",
"parentPublication": {
"id": "proceedings/icisce/2020/6406/0",
"title": "2020 7th International Conference on Information Science and Control Engineering (ICISCE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/01/09552856",
"title": "An Efficient Dual-Hierarchy t-SNE Minimization",
"doi": null,
"abstractUrl": "/journal/tg/2022/01/09552856/1xic3JUxdG8",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552856",
"articleId": "1xic3JUxdG8",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552233",
"articleId": "1xic56YNRyU",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBb23Bkg1O",
"name": "ttg202201-09552433s1-supp1-3114765.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552433s1-supp1-3114765.pdf",
"extension": "pdf",
"size": "4.97 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xic56YNRyU",
"doi": "10.1109/TVCG.2021.3114759",
"abstract": "N-ary relationships, which relate Z_$N$_Z entities where Z_$N$_Z is not necessarily two, can be visually represented as polygons whose vertices are the entities of the relationships. Manually generating a high-quality layout using this representation is labor-intensive. In this paper, we provide an automatic polygon layout generation algorithm for the visualization of N-ary relationships. At the core of our algorithm is a set of objective functions motivated by a number of design principles that we have identified. These objective functions are then used in an optimization framework that we develop to achieve high-quality layouts. Recognizing the duality between entities and relationships in the data, we provide a second visualization in which the roles of entities and relationships in the original data are reversed. This can lead to additional insight about the data. Furthermore, we enhance our framework for a joint optimization on the primal layout (original data) and the dual layout (where the roles of entities and relationships are reversed). This allows users to inspect their data using two complementary views. We apply our visualization approach to a number of datasets that include co-authorship data and social contact pattern data.",
"abstracts": [
{
"abstractType": "Regular",
"content": "N-ary relationships, which relate $N$ entities where $N$ is not necessarily two, can be visually represented as polygons whose vertices are the entities of the relationships. Manually generating a high-quality layout using this representation is labor-intensive. In this paper, we provide an automatic polygon layout generation algorithm for the visualization of N-ary relationships. At the core of our algorithm is a set of objective functions motivated by a number of design principles that we have identified. These objective functions are then used in an optimization framework that we develop to achieve high-quality layouts. Recognizing the duality between entities and relationships in the data, we provide a second visualization in which the roles of entities and relationships in the original data are reversed. This can lead to additional insight about the data. Furthermore, we enhance our framework for a joint optimization on the primal layout (original data) and the dual layout (where the roles of entities and relationships are reversed). This allows users to inspect their data using two complementary views. We apply our visualization approach to a number of datasets that include co-authorship data and social contact pattern data.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "N-ary relationships, which relate - entities where - is not necessarily two, can be visually represented as polygons whose vertices are the entities of the relationships. Manually generating a high-quality layout using this representation is labor-intensive. In this paper, we provide an automatic polygon layout generation algorithm for the visualization of N-ary relationships. At the core of our algorithm is a set of objective functions motivated by a number of design principles that we have identified. These objective functions are then used in an optimization framework that we develop to achieve high-quality layouts. Recognizing the duality between entities and relationships in the data, we provide a second visualization in which the roles of entities and relationships in the original data are reversed. This can lead to additional insight about the data. Furthermore, we enhance our framework for a joint optimization on the primal layout (original data) and the dual layout (where the roles of entities and relationships are reversed). This allows users to inspect their data using two complementary views. We apply our visualization approach to a number of datasets that include co-authorship data and social contact pattern data.",
"title": "Automatic Polygon Layout for Primal-Dual Visualization of Hypergraphs",
"normalizedTitle": "Automatic Polygon Layout for Primal-Dual Visualization of Hypergraphs",
"fno": "09552233",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Layout",
"Data Visualization",
"Optimization",
"Visualization",
"Manuals",
"Linear Programming",
"Electrical Engineering",
"Hypergraph Visualization",
"N Ary Relationships",
"Optimization",
"Polygon Layout",
"Duality",
"Primal Dual Visualization"
],
"authors": [
{
"givenName": "Botong",
"surname": "Qu",
"fullName": "Botong Qu",
"affiliation": "School of Electrical Engineering and Computer Science, Oregon State University, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Eugene",
"surname": "Zhang",
"fullName": "Eugene Zhang",
"affiliation": "School of Electrical Engineering and Computer Science, Oregon State University, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yue",
"surname": "Zhang",
"fullName": "Yue Zhang",
"affiliation": "School of Electrical Engineering and Computer Science, Oregon State University, United States",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "633-642",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/sec/2008/3348/0/3348a031",
"title": "Recognizing Geometric Path from Polygon-Based Integrated Circuit Layout",
"doi": null,
"abstractUrl": "/proceedings-article/sec/2008/3348a031/12OmNAoUTuW",
"parentPublication": {
"id": "proceedings/sec/2008/3348/0",
"title": "Embedded Computing, IEEE International Symposium on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdar/2011/4520/0/4520a508",
"title": "Layout Analysis for Historical Manuscripts Using Sift Features",
"doi": null,
"abstractUrl": "/proceedings-article/icdar/2011/4520a508/12OmNqIQS6r",
"parentPublication": {
"id": "proceedings/icdar/2011/4520/0",
"title": "2011 International Conference on Document Analysis and Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/focs/2011/4571/0/4571a492",
"title": "Markov Layout",
"doi": null,
"abstractUrl": "/proceedings-article/focs/2011/4571a492/12OmNqJ8tud",
"parentPublication": {
"id": "proceedings/focs/2011/4571/0",
"title": "2011 IEEE 52nd Annual Symposium on Foundations of Computer Science",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cad-graphics/2015/8020/0/07450427",
"title": "Facade Layout Symmetrization",
"doi": null,
"abstractUrl": "/proceedings-article/cad-graphics/2015/07450427/12OmNviHKiH",
"parentPublication": {
"id": "proceedings/cad-graphics/2015/8020/0",
"title": "2015 14th International Conference on Computer-Aided Design and Computer Graphics (CAD/Graphics)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wisa/2013/3218/0/06778637",
"title": "Trust Network Visualization Based on Force-Directed Layout",
"doi": null,
"abstractUrl": "/proceedings-article/wisa/2013/06778637/12OmNzYwc8h",
"parentPublication": {
"id": "proceedings/wisa/2013/3218/0",
"title": "2013 10th Web Information System and Application Conference (WISA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2016/01/07192690",
"title": "HOLA: Human-like Orthogonal Network Layout",
"doi": null,
"abstractUrl": "/journal/tg/2016/01/07192690/13rRUy0qnLI",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pacificvis/2022/2335/0/233500a061",
"title": "UNICON: A UNIform CONstraint Based Graph Layout Framework",
"doi": null,
"abstractUrl": "/proceedings-article/pacificvis/2022/233500a061/1E2wfeBklZS",
"parentPublication": {
"id": "proceedings/pacificvis/2022/2335/0",
"title": "2022 IEEE 15th Pacific Visualization Symposium (PacificVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2019/4803/0/480300h434",
"title": "Seq-SG2SL: Inferring Semantic Layout From Scene Graph Through Sequence to Sequence Learning",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2019/480300h434/1hVlTDVb5dK",
"parentPublication": {
"id": "proceedings/iccv/2019/4803/0",
"title": "2019 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/01/09556579",
"title": "STRATISFIMAL LAYOUT: A modular optimization model for laying out layered node-link network visualizations",
"doi": null,
"abstractUrl": "/journal/tg/2022/01/09556579/1xlw0LJ4OTm",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2021/4509/0/450900d731",
"title": "LayoutTransformer: Scene Layout Generation with Conceptual and Spatial Diversity",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2021/450900d731/1yeKJqXSUh2",
"parentPublication": {
"id": "proceedings/cvpr/2021/4509/0",
"title": "2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552433",
"articleId": "1xic8QCTZRe",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09552211",
"articleId": "1xic1bREyqY",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBaPEs3JN6",
"name": "ttg202201-09552233s1-supp2-3114759.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552233s1-supp2-3114759.pdf",
"extension": "pdf",
"size": "5.07 MB",
"__typename": "WebExtraType"
},
{
"id": "1zBaPP8hUfC",
"name": "ttg202201-09552233s1-supp1-3114759.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552233s1-supp1-3114759.mp4",
"extension": "mp4",
"size": "105 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |
{
"issue": {
"id": "1zBamVZHyne",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1xic1bREyqY",
"doi": "10.1109/TVCG.2021.3114822",
"abstract": "Reviewing a think-aloud video is both time-consuming and demanding as it requires UX (user experience) professionals to attend to many behavioral signals of the user in the video. Moreover, challenges arise when multiple UX professionals need to collaborate to reduce bias and errors. We propose a collaborative visual analytics tool, CoUX, to facilitate UX evaluators collectively reviewing think-aloud usability test videos of digital interfaces. CoUX seamlessly supports usability problem identification, annotation, and discussion in an integrated environment. To ease the discovery of usability problems, CoUX visualizes a set of problem-indicators based on acoustic, textual, and visual features extracted from the video and audio of a think-aloud session with machine learning. CoUX further enables collaboration amongst UX evaluators for logging, commenting, and consolidating the discovered problems with a chatbox-like user interface. We designed CoUX based on a formative study with two UX experts and insights derived from the literature. We conducted a user study with six pairs of UX practitioners on collaborative think-aloud video analysis tasks. The results indicate that CoUX is useful and effective in facilitating both problem identification and collaborative teamwork. We provide insights into how different features of CoUX were used to support both independent analysis and collaboration. Furthermore, our work highlights opportunities to improve collaborative usability test video analysis.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Reviewing a think-aloud video is both time-consuming and demanding as it requires UX (user experience) professionals to attend to many behavioral signals of the user in the video. Moreover, challenges arise when multiple UX professionals need to collaborate to reduce bias and errors. We propose a collaborative visual analytics tool, CoUX, to facilitate UX evaluators collectively reviewing think-aloud usability test videos of digital interfaces. CoUX seamlessly supports usability problem identification, annotation, and discussion in an integrated environment. To ease the discovery of usability problems, CoUX visualizes a set of problem-indicators based on acoustic, textual, and visual features extracted from the video and audio of a think-aloud session with machine learning. CoUX further enables collaboration amongst UX evaluators for logging, commenting, and consolidating the discovered problems with a chatbox-like user interface. We designed CoUX based on a formative study with two UX experts and insights derived from the literature. We conducted a user study with six pairs of UX practitioners on collaborative think-aloud video analysis tasks. The results indicate that CoUX is useful and effective in facilitating both problem identification and collaborative teamwork. We provide insights into how different features of CoUX were used to support both independent analysis and collaboration. Furthermore, our work highlights opportunities to improve collaborative usability test video analysis.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Reviewing a think-aloud video is both time-consuming and demanding as it requires UX (user experience) professionals to attend to many behavioral signals of the user in the video. Moreover, challenges arise when multiple UX professionals need to collaborate to reduce bias and errors. We propose a collaborative visual analytics tool, CoUX, to facilitate UX evaluators collectively reviewing think-aloud usability test videos of digital interfaces. CoUX seamlessly supports usability problem identification, annotation, and discussion in an integrated environment. To ease the discovery of usability problems, CoUX visualizes a set of problem-indicators based on acoustic, textual, and visual features extracted from the video and audio of a think-aloud session with machine learning. CoUX further enables collaboration amongst UX evaluators for logging, commenting, and consolidating the discovered problems with a chatbox-like user interface. We designed CoUX based on a formative study with two UX experts and insights derived from the literature. We conducted a user study with six pairs of UX practitioners on collaborative think-aloud video analysis tasks. The results indicate that CoUX is useful and effective in facilitating both problem identification and collaborative teamwork. We provide insights into how different features of CoUX were used to support both independent analysis and collaboration. Furthermore, our work highlights opportunities to improve collaborative usability test video analysis.",
"title": "CoUX: Collaborative Visual Analysis of Think-Aloud Usability Test Videos for Digital Interfaces",
"normalizedTitle": "CoUX: Collaborative Visual Analysis of Think-Aloud Usability Test Videos for Digital Interfaces",
"fno": "09552211",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Collaboration",
"Usability",
"Videos",
"Feature Extraction",
"Tools",
"Acoustics",
"Machine Learning",
"User Experience",
"Usability Problems",
"Think Aloud",
"Video Analysis",
"Machine Learning",
"Visual Analytics",
"Collaboration"
],
"authors": [
{
"givenName": "Ehsan Jahangirzadeh",
"surname": "Soure",
"fullName": "Ehsan Jahangirzadeh Soure",
"affiliation": "University of Waterloo, Canada",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Emily",
"surname": "Kuang",
"fullName": "Emily Kuang",
"affiliation": "Rochester Institute of Technology, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Mingming",
"surname": "Fan",
"fullName": "Mingming Fan",
"affiliation": "Rochester Institute of Technology, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jian",
"surname": "Zhao",
"fullName": "Jian Zhao",
"affiliation": "University of Waterloo, Canada",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "643-653",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/hcc/2002/1644/0/16440063",
"title": "Assertions in End-User Software Engineering: A Think-Aloud Study",
"doi": null,
"abstractUrl": "/proceedings-article/hcc/2002/16440063/12OmNqFJhX2",
"parentPublication": {
"id": "proceedings/hcc/2002/1644/0",
"title": "Proceedings IEEE 2002 Symposia on Human Centric Computing Languages and Environments",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ipcc/2005/9027/0/01494192",
"title": "Analyzing the interaction between facilitator and participants in two variants of the think-aloud method",
"doi": null,
"abstractUrl": "/proceedings-article/ipcc/2005/01494192/12OmNqNos9s",
"parentPublication": {
"id": "proceedings/ipcc/2005/9027/0",
"title": "2005 IEEE International Professional Communication Conference (IPCC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccea/2010/6079/1/05445788",
"title": "Why Thinking Aloud Matters for Usability Evaluation?",
"doi": null,
"abstractUrl": "/proceedings-article/iccea/2010/05445788/12OmNxEBzjY",
"parentPublication": {
"id": "proceedings/iccea/2010/6079/1",
"title": "2010 Second International Conference on Computer Engineering and Applications (ICCEA 2010)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ipcc/2005/9027/0/01494236",
"title": "Using eye tracking to address limitations in think-aloud protocol",
"doi": null,
"abstractUrl": "/proceedings-article/ipcc/2005/01494236/12OmNzUPpAh",
"parentPublication": {
"id": "proceedings/ipcc/2005/9027/0",
"title": "2005 IEEE International Professional Communication Conference (IPCC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vs-games/2018/7123/0/08493446",
"title": "Using Think-Aloud Protocol in Looking at the Framing of One's Character with a Case Study on Terraria",
"doi": null,
"abstractUrl": "/proceedings-article/vs-games/2018/08493446/14tNJndEsts",
"parentPublication": {
"id": "proceedings/vs-games/2018/7123/0",
"title": "2018 10th International Conference on Virtual Worlds and Games for Serious Applications (VS-Games)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fie/2022/6244/0/09962750",
"title": "Improving engineering students’ problem-solving skills through think-aloud exercises",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2022/09962750/1IHnBWIc9RC",
"parentPublication": {
"id": "proceedings/fie/2022/6244/0",
"title": "2022 IEEE Frontiers in Education Conference (FIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/conisoft/2022/6126/0/612600a168",
"title": "Using Think Aloud for Eliciting Requirements for a Reading Comprehension Software Tool",
"doi": null,
"abstractUrl": "/proceedings-article/conisoft/2022/612600a168/1LFLw98OgyQ",
"parentPublication": {
"id": "proceedings/conisoft/2022/6126/0",
"title": "2022 10th International Conference in Software Engineering Research and Innovation (CONISOFT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2020/01/08807301",
"title": "<bold>VisTA</bold>: Integrating Machine Intelligence with <bold>Vis</bold>ualization to Support the Investigation of <bold>T</bold>hink-<bold>A</bold>loud Sessions",
"doi": null,
"abstractUrl": "/journal/tg/2020/01/08807301/1cG6uY7sFEs",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fie/2019/1746/0/09028567",
"title": "Engineering Ph.D. Students’ Research Experiences: A Think-Aloud Study",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2019/09028567/1iffvltOibK",
"parentPublication": {
"id": "proceedings/fie/2019/1746/0",
"title": "2019 IEEE Frontiers in Education Conference (FIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icis-fall/2021/7679/0/09627365",
"title": "Assessing Computational Thinking Pedagogy in Serious Games Through Questionnaires, Think-aloud Testing, and Automated Data Logging",
"doi": null,
"abstractUrl": "/proceedings-article/icis-fall/2021/09627365/1z7dLTPd7nG",
"parentPublication": {
"id": "proceedings/icis-fall/2021/7679/0",
"title": "2021 IEEE/ACIS 20th International Fall Conference on Computer and Information Science (ICIS Fall)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09552233",
"articleId": "1xic56YNRyU",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09572234",
"articleId": "1xH5FXdMnoA",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1zBaETWukEM",
"name": "ttg202201-09552211s1-supp1-3114822.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202201-09552211s1-supp1-3114822.mp4",
"extension": "mp4",
"size": "41.3 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
} |