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{ "issue": { "id": "1y11mYZWHfO", "title": "Dec.", "year": "2021", "issueNum": "12", "idPrefix": "tg", "pubType": "journal", "volume": "27", "label": "Dec.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "1l6OgqspUL6", "doi": "10.1109/TVCG.2020.3006426", "abstract": "Although supercomputers are becoming increasingly powerful, their components have thus far not scaled proportionately. Compute power is growing enormously and is enabling finely resolved simulations that produce never-before-seen features. However, I/O capabilities lag by orders of magnitude, which means only a fraction of the simulation data can be stored for post hoc analysis. Prespecified plans for saving features and quantities of interest do not work for features that have not been seen before. Data-driven intelligent sampling schemes are needed to detect and save important parts of the simulation while it is running. Here, we propose a novel sampling scheme that reduces the size of the data by orders-of-magnitude while still preserving important regions. The approach we develop selects points with unusual data values and high gradients. We demonstrate that our approach outperforms traditional sampling schemes on a number of tasks.", "abstracts": [ { "abstractType": "Regular", "content": "Although supercomputers are becoming increasingly powerful, their components have thus far not scaled proportionately. Compute power is growing enormously and is enabling finely resolved simulations that produce never-before-seen features. However, I/O capabilities lag by orders of magnitude, which means only a fraction of the simulation data can be stored for post hoc analysis. Prespecified plans for saving features and quantities of interest do not work for features that have not been seen before. Data-driven intelligent sampling schemes are needed to detect and save important parts of the simulation while it is running. Here, we propose a novel sampling scheme that reduces the size of the data by orders-of-magnitude while still preserving important regions. The approach we develop selects points with unusual data values and high gradients. We demonstrate that our approach outperforms traditional sampling schemes on a number of tasks.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Although supercomputers are becoming increasingly powerful, their components have thus far not scaled proportionately. Compute power is growing enormously and is enabling finely resolved simulations that produce never-before-seen features. However, I/O capabilities lag by orders of magnitude, which means only a fraction of the simulation data can be stored for post hoc analysis. Prespecified plans for saving features and quantities of interest do not work for features that have not been seen before. Data-driven intelligent sampling schemes are needed to detect and save important parts of the simulation while it is running. Here, we propose a novel sampling scheme that reduces the size of the data by orders-of-magnitude while still preserving important regions. The approach we develop selects points with unusual data values and high gradients. We demonstrate that our approach outperforms traditional sampling schemes on a number of tasks.", "title": "Probabilistic Data-Driven Sampling via Multi-Criteria Importance Analysis", "normalizedTitle": "Probabilistic Data-Driven Sampling via Multi-Criteria Importance Analysis", "fno": "09130956", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Data Handling", "Probability", "Sampling Methods", "Probabilistic Data Driven Sampling", "Multicriteria Importance Analysis", "Supercomputers", "Compute Power", "Finely Resolved Simulations", "Simulation Data", "Post Hoc Analysis", "Prespecified Plans", "Data Driven Intelligent Sampling Schemes", "Orders Of Magnitude", "Important Regions", "Unusual Data Values", "Traditional Sampling Schemes", "Data Visualization", "Data Models", "Computational Modeling", "Task Analysis", "Sampling Methods", "Data Analysis", "Importance Sampling", "Data Reduction", "Error Quantification", "Feature Preservation" ], "authors": [ { "givenName": "Ayan", "surname": "Biswas", "fullName": "Ayan Biswas", "affiliation": "Los Alamos National Laboratory, Los Alamos, NM, USA", "__typename": "ArticleAuthorType" }, { "givenName": "Soumya", "surname": "Dutta", "fullName": "Soumya Dutta", "affiliation": "Los Alamos National Laboratory, Los Alamos, NM, USA", "__typename": "ArticleAuthorType" }, { "givenName": "Earl", "surname": "Lawrence", "fullName": "Earl Lawrence", "affiliation": "Los Alamos National Laboratory, Los Alamos, NM, USA", "__typename": "ArticleAuthorType" }, { "givenName": "John", "surname": "Patchett", "fullName": "John Patchett", "affiliation": "Los Alamos National Laboratory, Los Alamos, NM, USA", "__typename": "ArticleAuthorType" }, { "givenName": "Jon C.", "surname": "Calhoun", "fullName": "Jon C. Calhoun", "affiliation": "Clemson University, Clemson, SC, USA", "__typename": "ArticleAuthorType" }, { "givenName": "James", "surname": "Ahrens", "fullName": "James Ahrens", "affiliation": "Los Alamos National Laboratory, Los Alamos, NM, USA", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "12", "pubDate": "2021-12-01 00:00:00", "pubType": "trans", "pages": "4439-4454", "year": "2021", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/reldis/1994/6575/0/00336906", "title": "Probabilistic validation using worst event driven and importance sampling simulation", "doi": null, "abstractUrl": "/proceedings-article/reldis/1994/00336906/12OmNAGw15w", "parentPublication": { "id": "proceedings/reldis/1994/6575/0", "title": "Proceedings of IEEE 13th Symposium on Reliable Distributed Systems", 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"/proceedings-article/pccc/1991/00113852/12OmNx8wTop", "parentPublication": { "id": "proceedings/pccc/1991/2133/0", "title": "1991Tenth Annual International Phoenix Conference on Computers and Communications", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/mascots/2007/1853/0/04674415", "title": "Adaptive Sampling for Efficient MPSoC Architecture Simulation", "doi": null, "abstractUrl": "/proceedings-article/mascots/2007/04674415/12OmNzYNNgR", "parentPublication": { "id": "proceedings/mascots/2007/1853/0", "title": "2007 15th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/si/2018/01/08052534", "title": "Sparse Regression Driven Mixture Importance Sampling for Memory Design", "doi": null, "abstractUrl": "/journal/si/2018/01/08052534/13rRUxjQy9F", "parentPublication": { "id": "trans/si", "title": "IEEE Transactions on Very Large Scale Integration (VLSI) Systems", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2014/06/06671591", "title": "Importance Driven Environment Map Sampling", "doi": null, "abstractUrl": "/journal/tg/2014/06/06671591/13rRUxlgxTj", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tp/2019/12/08470977", "title": "Sparse One-Grab Sampling with Probabilistic Guarantees", "doi": null, "abstractUrl": "/journal/tp/2019/12/08470977/14Fq0VAriH9", "parentPublication": { "id": "trans/tp", "title": "IEEE Transactions on Pattern Analysis & Machine Intelligence", "__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" }, { "id": "proceedings/icpr/2021/8808/0/09413313", "title": "Low-Cost Lipschitz-Independent Adaptive Importance Sampling of Stochastic Gradients", "doi": null, "abstractUrl": "/proceedings-article/icpr/2021/09413313/1tmimgMil7a", "parentPublication": { "id": "proceedings/icpr/2021/8808/0", "title": "2020 25th International Conference on Pattern Recognition (ICPR)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "09507320", "articleId": "1vNfMheqZ2w", "__typename": "AdjacentArticleType" }, "next": { "fno": "09143452", "articleId": "1lxmwM0AM9O", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [ { "id": "1y11srcIzZK", "name": 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{ "issue": { "id": "1y11mYZWHfO", "title": "Dec.", "year": "2021", "issueNum": "12", "idPrefix": "tg", "pubType": "journal", "volume": "27", "label": "Dec.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "1lxmwM0AM9O", "doi": "10.1109/TVCG.2020.3010095", "abstract": "It is difficult to explore large text collections if no or little information is available on the contained documents. Hence, starting analytic tasks on such corpora is challenging for many stakeholders from various domains. As a remedy, recent visualization research suggests to use visual spatializations of representative text documents or tags to explore text collections. With PyramidTags, we introduce a novel approach for summarizing large text collections visually. In contrast to previous work, PyramidTags in particular aims at creating an improved representation that incorporates both temporal evolution and semantic relationship of visualized tags within the summarized document collection. As a result, it equips analysts with a visual starting point for interactive exploration to not only get an overview of the main terms and phrases of the corpus, but also to grasp important ideas and stories. Analysts can hover and select multiple tags to explore relationships and retrieve the most relevant documents. In this work, we apply PyramidTags to hundreds of thousands of web-crawled news reports. Our benchmarks suggest that PyramidTags creates time- and context-aware layouts, while preserving the inherent word order of important pairs.", "abstracts": [ { "abstractType": "Regular", "content": "It is difficult to explore large text collections if no or little information is available on the contained documents. Hence, starting analytic tasks on such corpora is challenging for many stakeholders from various domains. As a remedy, recent visualization research suggests to use visual spatializations of representative text documents or tags to explore text collections. With PyramidTags, we introduce a novel approach for summarizing large text collections visually. In contrast to previous work, PyramidTags in particular aims at creating an improved representation that incorporates both temporal evolution and semantic relationship of visualized tags within the summarized document collection. As a result, it equips analysts with a visual starting point for interactive exploration to not only get an overview of the main terms and phrases of the corpus, but also to grasp important ideas and stories. Analysts can hover and select multiple tags to explore relationships and retrieve the most relevant documents. In this work, we apply PyramidTags to hundreds of thousands of web-crawled news reports. Our benchmarks suggest that PyramidTags creates time- and context-aware layouts, while preserving the inherent word order of important pairs.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "It is difficult to explore large text collections if no or little information is available on the contained documents. Hence, starting analytic tasks on such corpora is challenging for many stakeholders from various domains. As a remedy, recent visualization research suggests to use visual spatializations of representative text documents or tags to explore text collections. With PyramidTags, we introduce a novel approach for summarizing large text collections visually. In contrast to previous work, PyramidTags in particular aims at creating an improved representation that incorporates both temporal evolution and semantic relationship of visualized tags within the summarized document collection. As a result, it equips analysts with a visual starting point for interactive exploration to not only get an overview of the main terms and phrases of the corpus, but also to grasp important ideas and stories. Analysts can hover and select multiple tags to explore relationships and retrieve the most relevant documents. In this work, we apply PyramidTags to hundreds of thousands of web-crawled news reports. Our benchmarks suggest that PyramidTags creates time- and context-aware layouts, while preserving the inherent word order of important pairs.", "title": "PyramidTags: Context-, Time- and Word Order-Aware Tag Maps to Explore Large Document Collections", "normalizedTitle": "PyramidTags: Context-, Time- and Word Order-Aware Tag Maps to Explore Large Document Collections", "fno": "09143452", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Data Visualisation", "Information Retrieval", "Internet", "Text Analysis", "Contained Documents", "Context Aware Layouts", "Document Collections", "Inherent Word Order", "Interactive Exploration", "Multiple Tags", "Pyramid Tags", "Representative Text Documents", "Summarized Document Collection", "Text Collections", "Time Word Order Aware Tag Maps", "Visual Spatializations", "Visual Starting Point", "Visualization Research", "Visualized Tags", "Web Crawled News Reports", "Tag Clouds", "Layout", "Data Visualization", "Text Mining", "Semantics", "Visual Analytics", "Information Retrieval", "Text Analysis", "Layout" ], "authors": [ { "givenName": "Johannes", "surname": "Knittel", "fullName": "Johannes Knittel", "affiliation": "Institute of Visualization and Interactive Systems, University of Stuttgart, Stuttgart, Germany", "__typename": "ArticleAuthorType" }, { "givenName": "Steffen", "surname": "Koch", "fullName": "Steffen Koch", "affiliation": "Institute of Visualization and Interactive Systems, University of Stuttgart, Stuttgart, Germany", "__typename": "ArticleAuthorType" }, { "givenName": "Thomas", "surname": "Ertl", "fullName": "Thomas Ertl", "affiliation": "Institute of Visualization and Interactive Systems, University of Stuttgart, Stuttgart, Germany", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "12", "pubDate": "2021-12-01 00:00:00", "pubType": "trans", "pages": "4455-4468", "year": "2021", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/iv/2015/7568/0/7568a114", "title": "Concentri Cloud: Word Cloud Visualization for Multiple Text Documents", "doi": null, "abstractUrl": "/proceedings-article/iv/2015/7568a114/12OmNA0dMO6", "parentPublication": { "id": "proceedings/iv/2015/7568/0", "title": "2015 19th International Conference on Information Visualisation (iV)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iv/2014/4103/0/4103a108", "title": "RadCloud: Visualizing Multiple Texts with Merged Word Clouds", "doi": null, "abstractUrl": "/proceedings-article/iv/2014/4103a108/12OmNAgY7my", "parentPublication": { "id": "proceedings/iv/2014/4103/0", "title": "2014 18th International Conference on Information Visualisation (IV)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/hicss/2014/2504/0/2504b833", "title": "Word Cloud Explorer: Text Analytics Based on Word Clouds", "doi": null, "abstractUrl": "/proceedings-article/hicss/2014/2504b833/12OmNqNG3jl", "parentPublication": { "id": "proceedings/hicss/2014/2504/0", "title": "2014 47th Hawaii International Conference on System Sciences (HICSS)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iv/2010/7846/0/05571243", "title": "Taggram: Exploring Geo-data on Maps through a Tag Cloud-Based Visualization", "doi": null, "abstractUrl": "/proceedings-article/iv/2010/05571243/12OmNvrdI4Y", "parentPublication": { "id": "proceedings/iv/2010/7846/0", "title": "2010 14th International Conference Information Visualisation", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/wi-iat/2009/3801/3/3801c129", "title": "Differential Tag Clouds: Highlighting Particular Features in Documents", "doi": null, "abstractUrl": "/proceedings-article/wi-iat/2009/3801c129/12OmNzayN1n", "parentPublication": { "id": "proceedings/wi-iat/2009/3801/3", "title": "Web Intelligence and Intelligent Agent Technology, IEEE/WIC/ACM International Conference on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2013/10/ttg2013101646", "title": "Combining Computational Analyses and Interactive Visualization for Document Exploration and Sensemaking in Jigsaw", "doi": null, "abstractUrl": "/journal/tg/2013/10/ttg2013101646/13rRUEgarjv", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "mags/cg/2010/06/mcg2010060042", "title": "Context-Preserving, Dynamic Word Cloud Visualization", "doi": null, "abstractUrl": "/magazine/cg/2010/06/mcg2010060042/13rRUwcAquA", "parentPublication": { "id": "mags/cg", "title": "IEEE Computer Graphics and Applications", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2015/12/07118241", "title": "Morphable Word Clouds for Time-Varying Text Data Visualization", "doi": null, "abstractUrl": "/journal/tg/2015/12/07118241/13rRUwfZBVn", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2018/06/08320795", "title": "Predominance Tag Maps", "doi": null, "abstractUrl": "/journal/tg/2018/06/08320795/13rRUwhHcJq", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iv/2018/7202/0/720200a122", "title": "Depth-Enhanced Tag Cloud Maps", "doi": null, "abstractUrl": "/proceedings-article/iv/2018/720200a122/17D45XeKgo7", "parentPublication": { "id": 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{ "issue": { "id": "1y11mYZWHfO", "title": "Dec.", "year": "2021", "issueNum": "12", "idPrefix": "tg", "pubType": "journal", "volume": "27", "label": "Dec.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "1l3ut5TpoCA", "doi": "10.1109/TVCG.2020.3005424", "abstract": "There is typically a trade-off between removing the detailed appearance (i.e., <italic>geometric textures</italic>) and preserving the intrinsic properties (i.e., <italic>geometric structures</italic>) of 3D surfaces. The conventional use of mesh vertex/facet-centered patches in many filters leads to side-effects including remnant textures, improperly filtered structures, and distorted shapes. We propose a selective guidance normal filter (SGNF) which adapts the Relative Total Variation (RTV) to a maximal/minimal scheme (mmRTV). The mmRTV measures the geometric flatness of surface patches, which helps in finding adaptive patches whose boundaries are aligned with the facet being processed. The adaptive patches provide selective guidance normals, which are subsequently used for normal filtering. The filtering smooths out the geometric textures by using guidance normals estimated from patches with maximal RTV (the least flatness), and preserves the geometric structures by using normals estimated from patches with minimal RTV (the most flatness). This simple yet effective modification of the RTV makes our SGNF specialized rather than trade off between texture removal and structure preservation, which is distinct from existing mesh filters. Experiments show that our approach is visually and numerically comparable to the state-of-the-art mesh filters, in most cases. In addition, the mmRTV is generally applicable to bas-relief modeling and image texture removal.", "abstracts": [ { "abstractType": "Regular", "content": "There is typically a trade-off between removing the detailed appearance (i.e., <italic>geometric textures</italic>) and preserving the intrinsic properties (i.e., <italic>geometric structures</italic>) of 3D surfaces. The conventional use of mesh vertex/facet-centered patches in many filters leads to side-effects including remnant textures, improperly filtered structures, and distorted shapes. We propose a selective guidance normal filter (SGNF) which adapts the Relative Total Variation (RTV) to a maximal/minimal scheme (mmRTV). The mmRTV measures the geometric flatness of surface patches, which helps in finding adaptive patches whose boundaries are aligned with the facet being processed. The adaptive patches provide selective guidance normals, which are subsequently used for normal filtering. The filtering smooths out the geometric textures by using guidance normals estimated from patches with maximal RTV (the least flatness), and preserves the geometric structures by using normals estimated from patches with minimal RTV (the most flatness). This simple yet effective modification of the RTV makes our SGNF specialized rather than trade off between texture removal and structure preservation, which is distinct from existing mesh filters. Experiments show that our approach is visually and numerically comparable to the state-of-the-art mesh filters, in most cases. In addition, the mmRTV is generally applicable to bas-relief modeling and image texture removal.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "There is typically a trade-off between removing the detailed appearance (i.e., geometric textures) and preserving the intrinsic properties (i.e., geometric structures) of 3D surfaces. The conventional use of mesh vertex/facet-centered patches in many filters leads to side-effects including remnant textures, improperly filtered structures, and distorted shapes. We propose a selective guidance normal filter (SGNF) which adapts the Relative Total Variation (RTV) to a maximal/minimal scheme (mmRTV). The mmRTV measures the geometric flatness of surface patches, which helps in finding adaptive patches whose boundaries are aligned with the facet being processed. The adaptive patches provide selective guidance normals, which are subsequently used for normal filtering. The filtering smooths out the geometric textures by using guidance normals estimated from patches with maximal RTV (the least flatness), and preserves the geometric structures by using normals estimated from patches with minimal RTV (the most flatness). This simple yet effective modification of the RTV makes our SGNF specialized rather than trade off between texture removal and structure preservation, which is distinct from existing mesh filters. Experiments show that our approach is visually and numerically comparable to the state-of-the-art mesh filters, in most cases. In addition, the mmRTV is generally applicable to bas-relief modeling and image texture removal.", "title": "Selective Guidance Normal Filter for Geometric Texture Removal", "normalizedTitle": "Selective Guidance Normal Filter for Geometric Texture Removal", "fno": "09127881", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Computer Graphics", "Image Filtering", "Image Texture", "Stereo Image Processing", "Geometric Texture Removal", "Geometric Structures", "Remnant Textures", "Improperly Filtered Structures", "Selective Guidance Normal Filter", "Mm RTV", "Geometric Flatness", "Surface Patches", "Adaptive Patches", "Selective Guidance Normals", "Normal Filtering", "Maximal RTV", "Minimal RTV", "Structure Preservation", "Mesh Filters", "Bas Relief Modeling", "Image Texture Removal", "SGNF", "Mesh Vertex Facet Centered Patches", "Relative Total Variation", "3 D Surfaces", "Maximal Minimal Scheme", "Surface Treatment", "Three Dimensional Displays", "Surface Texture", "Smoothing Methods", "Geometry", "Tensors", "Noise Reduction", "Geometry Filtering", "Selective Guidance", "Geometric Texture Removal", "Mm RTV", "Bas Relief Modeling" ], "authors": [ { "givenName": "Mingqiang", "surname": "Wei", "fullName": "Mingqiang Wei", "affiliation": "Nanjing University of Aeronautics and Astronautics, Nanjing, China", "__typename": "ArticleAuthorType" }, { "givenName": "Yidan", "surname": "Feng", "fullName": "Yidan Feng", "affiliation": "Nanjing University of Aeronautics and Astronautics, Nanjing, China", "__typename": "ArticleAuthorType" }, { "givenName": "Honghua", "surname": "Chen", "fullName": "Honghua Chen", "affiliation": "Nanjing University of Aeronautics and Astronautics, Nanjing, China", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "12", "pubDate": "2021-12-01 00:00:00", "pubType": "trans", "pages": "4469-4482", "year": "2021", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/icpr/2014/5209/0/5209b126", "title": "3D Facial Skin Texture Analysis Using Geometric Descriptors", "doi": null, "abstractUrl": "/proceedings-article/icpr/2014/5209b126/12OmNCesr5j", "parentPublication": { "id": "proceedings/icpr/2014/5209/0", "title": "2014 22nd International Conference on Pattern Recognition (ICPR)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iccv/2017/1032/0/1032c344", "title": "3D Surface Detail Enhancement from a Single Normal Map", "doi": null, "abstractUrl": "/proceedings-article/iccv/2017/1032c344/12OmNwCsdKG", "parentPublication": { "id": "proceedings/iccv/2017/1032/0", "title": "2017 IEEE International Conference on Computer Vision (ICCV)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/pbg/2005/20/0/01500326", "title": "Conversion of point-sampled 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{ "issue": { "id": "1y11mYZWHfO", "title": "Dec.", "year": "2021", "issueNum": "12", "idPrefix": "tg", "pubType": "journal", "volume": "27", "label": "Dec.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "1wpqubOKAne", "doi": "10.1109/TVCG.2021.3107597", "abstract": "Multi-scale granular materials, such as powdered materials and mudslides, are pretty common in nature. Modeling such materials and their phase transitions remains challenging since this task involves the delicate representations of various ranges of particles with multiple scales that cause their property variations among liquid, granular solid (i.e., particles), and smoke-like materials. To effectively animate the complicated yet intriguing natural phenomena involving multi-scale granular materials and their phase transitions in graphics with high fidelity, this article advocates a hybrid Euler-Lagrange solver to handle the behaviors of involved discontinuous fluid-like materials faithfully. At the algorithmic level, we present a unified framework that tightly couples the affine particle-in-cell (APIC) solver with density field to achieve the transformation spanning across granular particles, dust cloud, powders, and their natural mixtures. For example, a part of the granular particles could be transformed into dust cloud while interacting with air and being represented by density field. Meanwhile, the velocity decrease of the involved materials could also result in the transit from the density-field-driven dust to powder particles. Besides, to further enhance our modeling and simulation power to broaden the range of multi-scale materials, we introduce a moisture property for granular particles to control the transitions between particles and viscous liquid. At the geometric level, we devise an additional surface-tracking procedure to simulate the viscous liquid phase. We can arrive at delicate viscous behaviors by controlling the corresponding yield conditions. Through various experiments with the different scenes design being conducted in our unified framework, we can validate the mixed multi-scale materials&#x2019; mutual transformation processes. Our unified framework furnished with a hybrid solver can significantly enhance the modeling flexibility and the animation potential of the particle-grid hybrid materials in graphics.", "abstracts": [ { "abstractType": "Regular", "content": "Multi-scale granular materials, such as powdered materials and mudslides, are pretty common in nature. Modeling such materials and their phase transitions remains challenging since this task involves the delicate representations of various ranges of particles with multiple scales that cause their property variations among liquid, granular solid (i.e., particles), and smoke-like materials. To effectively animate the complicated yet intriguing natural phenomena involving multi-scale granular materials and their phase transitions in graphics with high fidelity, this article advocates a hybrid Euler-Lagrange solver to handle the behaviors of involved discontinuous fluid-like materials faithfully. At the algorithmic level, we present a unified framework that tightly couples the affine particle-in-cell (APIC) solver with density field to achieve the transformation spanning across granular particles, dust cloud, powders, and their natural mixtures. For example, a part of the granular particles could be transformed into dust cloud while interacting with air and being represented by density field. Meanwhile, the velocity decrease of the involved materials could also result in the transit from the density-field-driven dust to powder particles. Besides, to further enhance our modeling and simulation power to broaden the range of multi-scale materials, we introduce a moisture property for granular particles to control the transitions between particles and viscous liquid. At the geometric level, we devise an additional surface-tracking procedure to simulate the viscous liquid phase. We can arrive at delicate viscous behaviors by controlling the corresponding yield conditions. Through various experiments with the different scenes design being conducted in our unified framework, we can validate the mixed multi-scale materials&#x2019; mutual transformation processes. Our unified framework furnished with a hybrid solver can significantly enhance the modeling flexibility and the animation potential of the particle-grid hybrid materials in graphics.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Multi-scale granular materials, such as powdered materials and mudslides, are pretty common in nature. Modeling such materials and their phase transitions remains challenging since this task involves the delicate representations of various ranges of particles with multiple scales that cause their property variations among liquid, granular solid (i.e., particles), and smoke-like materials. To effectively animate the complicated yet intriguing natural phenomena involving multi-scale granular materials and their phase transitions in graphics with high fidelity, this article advocates a hybrid Euler-Lagrange solver to handle the behaviors of involved discontinuous fluid-like materials faithfully. At the algorithmic level, we present a unified framework that tightly couples the affine particle-in-cell (APIC) solver with density field to achieve the transformation spanning across granular particles, dust cloud, powders, and their natural mixtures. For example, a part of the granular particles could be transformed into dust cloud while interacting with air and being represented by density field. Meanwhile, the velocity decrease of the involved materials could also result in the transit from the density-field-driven dust to powder particles. Besides, to further enhance our modeling and simulation power to broaden the range of multi-scale materials, we introduce a moisture property for granular particles to control the transitions between particles and viscous liquid. At the geometric level, we devise an additional surface-tracking procedure to simulate the viscous liquid phase. We can arrive at delicate viscous behaviors by controlling the corresponding yield conditions. Through various experiments with the different scenes design being conducted in our unified framework, we can validate the mixed multi-scale materials’ mutual transformation processes. Our unified framework furnished with a hybrid solver can significantly enhance the modeling flexibility and the animation potential of the particle-grid hybrid materials in graphics.", "title": "Simulating Multi-Scale, Granular Materials and Their Transitions With a Hybrid Euler-Lagrange Solver", "normalizedTitle": "Simulating Multi-Scale, Granular Materials and Their Transitions With a Hybrid Euler-Lagrange Solver", "fno": "09524524", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Computational Fluid Dynamics", "Computer Animation", "Flow Simulation", "Granular Materials", "Numerical Analysis", "Two Phase Flow", "Granular Particles", "Dust Cloud", "Density Field", "Involved Materials", "Density Field Driven Dust", "Powder Particles", "Viscous Liquid Phase", "Mixed Multiscale Materials", "Hybrid Solver", "Particle Grid Hybrid Materials", "Hybrid Euler Lagrange Solver", "Multiscale Granular Materials", "Powdered Materials", "Phase Transitions", "Complicated Yet Intriguing Natural Phenomena", "Involved Discontinuous Fluid Like", "Affine Particle In Cell Solver", "Liquids", "Computational Modeling", "Mathematical Model", "Atmospheric Modeling", "Moisture", "Surface Treatment", "Multi Scale Materials", "Granular Particles", "Density Field Based Dust Cloud", "Viscous Liquid", "APIC" ], "authors": [ { "givenName": "Yang", "surname": "Gao", "fullName": "Yang Gao", "affiliation": "State Key Laboratory of Virtual Reality Technology and Systems, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, China", "__typename": "ArticleAuthorType" }, { "givenName": "Shuai", "surname": "Li", "fullName": "Shuai Li", "affiliation": "State Key Laboratory of Virtual Reality Technology and Systems, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, China", "__typename": "ArticleAuthorType" }, { "givenName": "Aimin", "surname": "Hao", "fullName": "Aimin Hao", "affiliation": "State Key Laboratory of Virtual Reality Technology and Systems, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, China", "__typename": "ArticleAuthorType" }, { "givenName": "Hong", "surname": "Qin", "fullName": "Hong Qin", "affiliation": "Department of Computer Science, Stony Brook University, Stony Brook, NY, USA", "__typename": "ArticleAuthorType" } ], "replicability": { "isEnabled": true, "codeDownloadUrl": "https://github.com/gaoyangVR/MultiScale-Gracular-APIC.git", "codeRepositoryUrl": "https://github.com/gaoyangVR/MultiScale-Gracular-APIC", "__typename": "ArticleReplicabilityType" }, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "12", "pubDate": "2021-12-01 00:00:00", "pubType": "trans", "pages": "4483-4494", "year": "2021", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/cgiv/2008/3359/0/3359a028", "title": "Real-Time Simulation of 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{ "issue": { "id": "1y11mYZWHfO", "title": "Dec.", "year": "2021", "issueNum": "12", "idPrefix": "tg", "pubType": "journal", "volume": "27", "label": "Dec.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "1kHUKlOoA4U", "doi": "10.1109/TVCG.2020.3002950", "abstract": "Sketching is one common approach to query time series data for patterns of interest. Most existing solutions for matching the data with the interaction are based on an empirically modeled similarity function between the user&#x2019;s sketch and the time series data with limited efficiency and accuracy. In this article, we introduce a machine learning based solution for fast and accurate querying of time series data based on a swift sketching interaction. We build on existing LSTM technology (long short-term memory) to encode both the sketch and the time series data in a network with shared parameters. We use data from a user study to let the network learn a proper similarity function. We focus our approach on perceived similarities and achieve that the learned model also includes a user-side aspect. To the best of our knowledge, this is the first data-driven solution for querying time series data in visual analytics. Besides evaluating the accuracy and efficiency directly in a quantitative way, we also compare our solution to the recently published Qetch algorithm as well as the commonly used dynamic time warping (DTW) algorithm.", "abstracts": [ { "abstractType": "Regular", "content": "Sketching is one common approach to query time series data for patterns of interest. Most existing solutions for matching the data with the interaction are based on an empirically modeled similarity function between the user&#x2019;s sketch and the time series data with limited efficiency and accuracy. In this article, we introduce a machine learning based solution for fast and accurate querying of time series data based on a swift sketching interaction. We build on existing LSTM technology (long short-term memory) to encode both the sketch and the time series data in a network with shared parameters. We use data from a user study to let the network learn a proper similarity function. We focus our approach on perceived similarities and achieve that the learned model also includes a user-side aspect. To the best of our knowledge, this is the first data-driven solution for querying time series data in visual analytics. Besides evaluating the accuracy and efficiency directly in a quantitative way, we also compare our solution to the recently published Qetch algorithm as well as the commonly used dynamic time warping (DTW) algorithm.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Sketching is one common approach to query time series data for patterns of interest. Most existing solutions for matching the data with the interaction are based on an empirically modeled similarity function between the user’s sketch and the time series data with limited efficiency and accuracy. In this article, we introduce a machine learning based solution for fast and accurate querying of time series data based on a swift sketching interaction. We build on existing LSTM technology (long short-term memory) to encode both the sketch and the time series data in a network with shared parameters. We use data from a user study to let the network learn a proper similarity function. We focus our approach on perceived similarities and achieve that the learned model also includes a user-side aspect. To the best of our knowledge, this is the first data-driven solution for querying time series data in visual analytics. Besides evaluating the accuracy and efficiency directly in a quantitative way, we also compare our solution to the recently published Qetch algorithm as well as the commonly used dynamic time warping (DTW) algorithm.", "title": "Sketch-Based Fast and Accurate Querying of Time Series Using Parameter-Sharing LSTM Networks", "normalizedTitle": "Sketch-Based Fast and Accurate Querying of Time Series Using Parameter-Sharing LSTM Networks", "fno": "09119141", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Data Visualisation", "Learning Artificial Intelligence", "Query Processing", "Time Series", "Sketch Based Fast", "Accurate Querying", "Parameter Sharing LSTM Networks", "Sketching", "Time Series Data", "Data Driven Solution", "Time Series Analysis", "Machine Learning", "Time Series Analysis", "Data Visualization", "Data Models", "Heuristic Algorithms", "Machine Learning", "Sketch Based Interaction", "Visual Analytics", "Time Series Data" ], "authors": [ { "givenName": "Chaoran", "surname": "Fan", "fullName": "Chaoran Fan", "affiliation": "University of Bergen, Bergen, Norway", "__typename": "ArticleAuthorType" }, { "givenName": "Krešimir", "surname": "Matković", "fullName": "Krešimir Matković", "affiliation": "VRVis Research Center, Wien, Austria", "__typename": "ArticleAuthorType" }, { "givenName": "Helwig", "surname": "Hauser", "fullName": "Helwig Hauser", "affiliation": "University of Bergen, Bergen, Norway", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "12", "pubDate": "2021-12-01 00:00:00", "pubType": "trans", "pages": "4495-4506", "year": "2021", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/vast/2014/6227/0/07042522", "title": "A sketch+fisheye interface for visual analytics of large time-series", "doi": null, "abstractUrl": 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{ "issue": { "id": "1y11mYZWHfO", "title": "Dec.", "year": "2021", "issueNum": "12", "idPrefix": "tg", "pubType": "journal", "volume": "27", "label": "Dec.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "1kTxx2qV6zm", "doi": "10.1109/TVCG.2020.3004137", "abstract": "We introduce <italic>Tilt Map</italic>, a novel interaction technique for intuitively transitioning between 2D and 3D map visualisations in immersive environments. Our focus is visualising data associated with areal features on maps, for example, population density by state. <italic>Tilt Map</italic> transitions from 2D choropleth maps to 3D prism maps to 2D bar charts to overcome the limitations of each. Our article includes two user studies. The first study compares subjects&#x2019; task performance interpreting population density data using 2D choropleth maps and 3D prism maps in virtual reality (VR). We observed greater task accuracy with prism maps, but faster response times with choropleth maps. The complementarity of these views inspired our hybrid <italic>Tilt Map</italic> design. Our second study compares <italic>Tilt Map</italic> to: a side-by-side arrangement of the various views; and interactive toggling between views. The results indicate benefits for <italic>Tilt Map</italic> in user preference; and accuracy (versus side-by-side) and time (versus toggle).", "abstracts": [ { "abstractType": "Regular", "content": "We introduce <italic>Tilt Map</italic>, a novel interaction technique for intuitively transitioning between 2D and 3D map visualisations in immersive environments. Our focus is visualising data associated with areal features on maps, for example, population density by state. <italic>Tilt Map</italic> transitions from 2D choropleth maps to 3D prism maps to 2D bar charts to overcome the limitations of each. Our article includes two user studies. The first study compares subjects&#x2019; task performance interpreting population density data using 2D choropleth maps and 3D prism maps in virtual reality (VR). We observed greater task accuracy with prism maps, but faster response times with choropleth maps. The complementarity of these views inspired our hybrid <italic>Tilt Map</italic> design. Our second study compares <italic>Tilt Map</italic> to: a side-by-side arrangement of the various views; and interactive toggling between views. The results indicate benefits for <italic>Tilt Map</italic> in user preference; and accuracy (versus side-by-side) and time (versus toggle).", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "We introduce Tilt Map, a novel interaction technique for intuitively transitioning between 2D and 3D map visualisations in immersive environments. Our focus is visualising data associated with areal features on maps, for example, population density by state. Tilt Map transitions from 2D choropleth maps to 3D prism maps to 2D bar charts to overcome the limitations of each. Our article includes two user studies. The first study compares subjects’ task performance interpreting population density data using 2D choropleth maps and 3D prism maps in virtual reality (VR). We observed greater task accuracy with prism maps, but faster response times with choropleth maps. The complementarity of these views inspired our hybrid Tilt Map design. Our second study compares Tilt Map to: a side-by-side arrangement of the various views; and interactive toggling between views. The results indicate benefits for Tilt Map in user preference; and accuracy (versus side-by-side) and time (versus toggle).", "title": "Tilt Map: Interactive Transitions Between Choropleth Map, Prism Map and Bar Chart in Immersive Environments", "normalizedTitle": "Tilt Map: Interactive Transitions Between Choropleth Map, Prism Map and Bar Chart in Immersive Environments", "fno": "09123548", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Cartography", "Data Visualisation", "Geographic Information Systems", "Virtual Reality", "Immersive Environments", "Tilt Map Transitions", "Choropleth Maps", "Prism Maps", "2 D Bar Charts", "Hybrid Tilt Map", "Choropleth Map", "Prism Map", "3 D Map Visualisations", "Data Visualization", "Task Analysis", "Three Dimensional Displays", "Two Dimensional Displays", "Augmented Reality", "Social Factors", "Statistics", "Immersive Analytics", "Mixed Augmented Reality", "Virtual Reality", "Geographic Visualization", "Interaction Techniques" ], "authors": [ { "givenName": "Yalong", "surname": "Yang", "fullName": "Yalong Yang", "affiliation": "School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA", "__typename": "ArticleAuthorType" }, { "givenName": "Tim", "surname": "Dwyer", "fullName": "Tim Dwyer", "affiliation": "Department of Human-Centred Computing, Faculty of Information Technology, Monash University, Clayton, VIC, Australia", "__typename": "ArticleAuthorType" }, { "givenName": "Kim", "surname": "Marriott", "fullName": "Kim Marriott", "affiliation": "Department of Human-Centred Computing, Faculty of Information Technology, Monash University, Clayton, VIC, Australia", "__typename": "ArticleAuthorType" }, { "givenName": "Bernhard", "surname": "Jenny", "fullName": "Bernhard Jenny", "affiliation": "Department of Human-Centred Computing, Faculty of Information Technology, Monash University, Clayton, VIC, Australia", "__typename": "ArticleAuthorType" }, { "givenName": "Sarah", "surname": "Goodwin", "fullName": "Sarah Goodwin", "affiliation": "Department of Human-Centred Computing, Faculty of Information Technology, Monash University, Clayton, VIC, Australia", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "12", "pubDate": "2021-12-01 00:00:00", "pubType": "trans", "pages": "4507-4519", "year": "2021", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/hldvt/2016/4270/0/07748257", "title": "Modeling, programming and performance analysis of automotive environment map representations on embedded GPUs", "doi": null, "abstractUrl": "/proceedings-article/hldvt/2016/07748257/12OmNqG0SIc", "parentPublication": { "id": "proceedings/hldvt/2016/4270/0", "title": "2016 IEEE International High Level Design Validation and Test Workshop (HLDVT)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iv/2001/1195/0/11950757", "title": "Dynamic Queries and Brushing on Choropleth Maps", "doi": null, "abstractUrl": "/proceedings-article/iv/2001/11950757/12OmNwdbVac", "parentPublication": { "id": "proceedings/iv/2001/1195/0", "title": "Proceedings Fifth International Conference on Information Visualisation", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iih-msp/2008/3278/0/3278b340", "title": "A Novel Symmetric Image Encryption Approach Based on a New Invertible Two-Dimensional Map", "doi": null, "abstractUrl": "/proceedings-article/iih-msp/2008/3278b340/12OmNzxgHHy", "parentPublication": { "id": "proceedings/iih-msp/2008/3278/0", "title": "2008 Fourth International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/cvpr/2018/6420/0/642000h093", "title": "UV-GAN: Adversarial Facial UV Map Completion for Pose-Invariant Face Recognition", "doi": null, "abstractUrl": "/proceedings-article/cvpr/2018/642000h093/17D45WWzW3C", "parentPublication": { "id": "proceedings/cvpr/2018/6420/0", "title": "2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icmeas/2022/6305/0/630500a236", "title": "Research on 3D modeling of UAV tilt photogrammetry", "doi": null, "abstractUrl": "/proceedings-article/icmeas/2022/630500a236/1I8wAd85WGQ", "parentPublication": { "id": "proceedings/icmeas/2022/6305/0", "title": "2022 8th International Conference on Mechanical Engineering and Automation Science (ICMEAS)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/hpcc-smartcity-dss/2019/2058/0/205800a774", "title": "2D Henon-Chebyshev Chaotic Map for Image Encryption", "doi": null, 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Visualization of 2D Morse Complex Ensembles Using Statistical Summary Maps", "doi": null, "abstractUrl": "/journal/tg/2022/04/09187994/1mXkiNpxvvq", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2021/02/09222248", "title": "Topology Density Map for Urban Data Visualization and Analysis", "doi": null, "abstractUrl": "/journal/tg/2021/02/09222248/1nTr0CUpIIM", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2022/07/09249052", "title": "Rainbow Dash: Intuitiveness, Interpretability and Memorability of the Rainbow Color Scheme in Visualization", "doi": null, "abstractUrl": "/journal/tg/2022/07/09249052/1ovEVPWDI4g", "parentPublication": { "id": "trans/tg", "title": "IEEE 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{ "issue": { "id": "1y11mYZWHfO", "title": "Dec.", "year": "2021", "issueNum": "12", "idPrefix": "tg", "pubType": "journal", "volume": "27", "label": "Dec.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "1kRRC5VRVMQ", "doi": "10.1109/TVCG.2020.3003994", "abstract": "This article introduces a novel approach to generate visually promising skeletons automatically without any manual tuning. In practice, it is challenging to extract promising skeletons directly using existing approaches. This is because they either cannot fully preserve shape features, or require manual intervention, such as boundary smoothing and skeleton pruning, to justify the eye-level view assumption. We propose an approach here that generates backbone and dense skeletons by shape input, and then extends the backbone branches via skeleton grafting from the dense skeleton to ensure a well-integrated output. Based on our evaluation, the generated skeletons best depict the shapes at levels that are similar to human perception. To evaluate and fully express the properties of the extracted skeletons, we introduce two potential functions within the high-order matching protocol to improve the accuracy of skeleton-based matching. These two functions fuse the similarities between skeleton graphs and geometrical relations characterized by multiple skeleton endpoints. Experiments on three high-order matching protocols show that the proposed potential functions can effectively reduce the number of incorrect matches.", "abstracts": [ { "abstractType": "Regular", "content": "This article introduces a novel approach to generate visually promising skeletons automatically without any manual tuning. In practice, it is challenging to extract promising skeletons directly using existing approaches. This is because they either cannot fully preserve shape features, or require manual intervention, such as boundary smoothing and skeleton pruning, to justify the eye-level view assumption. We propose an approach here that generates backbone and dense skeletons by shape input, and then extends the backbone branches via skeleton grafting from the dense skeleton to ensure a well-integrated output. Based on our evaluation, the generated skeletons best depict the shapes at levels that are similar to human perception. To evaluate and fully express the properties of the extracted skeletons, we introduce two potential functions within the high-order matching protocol to improve the accuracy of skeleton-based matching. These two functions fuse the similarities between skeleton graphs and geometrical relations characterized by multiple skeleton endpoints. Experiments on three high-order matching protocols show that the proposed potential functions can effectively reduce the number of incorrect matches.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "This article introduces a novel approach to generate visually promising skeletons automatically without any manual tuning. In practice, it is challenging to extract promising skeletons directly using existing approaches. This is because they either cannot fully preserve shape features, or require manual intervention, such as boundary smoothing and skeleton pruning, to justify the eye-level view assumption. We propose an approach here that generates backbone and dense skeletons by shape input, and then extends the backbone branches via skeleton grafting from the dense skeleton to ensure a well-integrated output. Based on our evaluation, the generated skeletons best depict the shapes at levels that are similar to human perception. To evaluate and fully express the properties of the extracted skeletons, we introduce two potential functions within the high-order matching protocol to improve the accuracy of skeleton-based matching. These two functions fuse the similarities between skeleton graphs and geometrical relations characterized by multiple skeleton endpoints. Experiments on three high-order matching protocols show that the proposed potential functions can effectively reduce the number of incorrect matches.", "title": "Towards Automatic Skeleton Extraction With Skeleton Grafting", "normalizedTitle": "Towards Automatic Skeleton Extraction With Skeleton Grafting", "fno": "09122436", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Feature Extraction", "Graph Theory", "Image Matching", "Skeleton Graphs", "Multiple Skeleton Endpoints", "Potential Functions", "Skeleton Grafting", "Visually Promising Skeletons", "Manual Tuning", "Shape Features", "Boundary Smoothing", "Skeleton Pruning", "Eye Level View Assumption", "Dense Skeleton", "Generated Skeletons", "Extracted Skeletons", "Automatic Skeleton Extraction", "High Order Matching Protocol", "Skeleton", "Solid Modeling", "Bayes Methods", "Tuning", "Feature Extraction", "Skeleton Extraction", "Skeleton Matching", "Shape Matching", "Skeleton Grafting", "High Order Matching" ], "authors": [ { "givenName": "Cong", "surname": "Yang", "fullName": "Cong Yang", "affiliation": "Institute for Vision and Graphics, University of Siegen, Siegen, Germany", "__typename": "ArticleAuthorType" }, { "givenName": "Bipin", "surname": "Indurkhya", "fullName": "Bipin Indurkhya", "affiliation": "Computer Science and Cognitive Science Departments, Jagiellonian University, Cracow, Poland", "__typename": "ArticleAuthorType" }, { "givenName": "John", "surname": "See", "fullName": "John See", "affiliation": "Faculty of Computing and Informatics, Multimedia University, Cyberjaya, Selangor, Malaysia", "__typename": "ArticleAuthorType" }, { "givenName": "Marcin", "surname": "Grzegorzek", "fullName": "Marcin Grzegorzek", "affiliation": "Institute of Medical Informatics, University of Lübeck, Lübeck, Germany", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "12", "pubDate": "2021-12-01 00:00:00", 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on Big Data (Big Data)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2008/04/ttg2008040926", "title": "Curve-Skeleton Extraction Using Iterative Least Squares Optimization", "doi": null, "abstractUrl": "/journal/tg/2008/04/ttg2008040926/13rRUxASuGa", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tp/2007/03/i0449", "title": "Skeleton Pruning by Contour Partitioning with Discrete Curve Evolution", "doi": null, "abstractUrl": "/journal/tp/2007/03/i0449/13rRUxDqS57", "parentPublication": { "id": "trans/tp", "title": "IEEE Transactions on Pattern Analysis & Machine Intelligence", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "mags/cg/1995/02/mcg1995020044", "title": "Shape Blending Using the Star-Skeleton Representation", "doi": null, 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{ "issue": { "id": "1y11mYZWHfO", "title": "Dec.", "year": "2021", "issueNum": "12", "idPrefix": "tg", "pubType": "journal", "volume": "27", "label": "Dec.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "1y11rHAppWU", "doi": "10.1109/TVCG.2021.3119084", "abstract": "Presents a listing of reviewers who contributed to this publication in 2021.", "abstracts": [ { "abstractType": "Regular", "content": "Presents a listing of reviewers who contributed to this publication in 2021.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Presents a listing of reviewers who contributed to this publication in 2021.", "title": "2021 Reviewers List", "normalizedTitle": "2021 Reviewers List", "fno": "09586409", "hasPdf": true, "idPrefix": "tg", "keywords": [], "authors": [], "replicability": null, "showBuyMe": false, "showRecommendedArticles": false, "isOpenAccess": true, "issueNum": "12", "pubDate": "2021-12-01 00:00:00", "pubType": "trans", "pages": "4533-4539", "year": "2021", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [], "adjacentArticles": { "previous": { "fno": "09122436", "articleId": "1kRRC5VRVMQ", "__typename": "AdjacentArticleType" }, "next": null, "__typename": "AdjacentArticlesType" }, "webExtras": [], "articleVideos": [] }
{ "issue": { "id": "1zKXryr0JDG", "title": "Feb.", "year": "2022", "issueNum": "02", "idPrefix": "tg", "pubType": "journal", "volume": "28", "label": "Feb.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "1lxmsQXZ36U", "doi": "10.1109/TVCG.2020.3009949", "abstract": "In the animation industry, the colorization of raw sketch images is a vitally important but very time-consuming task. This article focuses on providing a novel solution that semiautomatically colorizes a set of images using a single colorized reference image. Our method is able to provide coherent colors for regions that have similar semantics to those in the reference image. An active-learning-based framework is used to match local regions, followed by mixed-integer quadratic programming (MIQP) which considers the spatial contexts to further refine the matching results. We efficiently utilize user interactions to achieve high accuracy in the final colorized images. Experiments show that our method outperforms the current state-of-the-art deep learning based colorization method in terms of color coherency with the reference image. The region matching framework could potentially be applied to other applications, such as color transfer.", "abstracts": [ { "abstractType": "Regular", "content": "In the animation industry, the colorization of raw sketch images is a vitally important but very time-consuming task. This article focuses on providing a novel solution that semiautomatically colorizes a set of images using a single colorized reference image. Our method is able to provide coherent colors for regions that have similar semantics to those in the reference image. An active-learning-based framework is used to match local regions, followed by mixed-integer quadratic programming (MIQP) which considers the spatial contexts to further refine the matching results. We efficiently utilize user interactions to achieve high accuracy in the final colorized images. Experiments show that our method outperforms the current state-of-the-art deep learning based colorization method in terms of color coherency with the reference image. The region matching framework could potentially be applied to other applications, such as color transfer.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "In the animation industry, the colorization of raw sketch images is a vitally important but very time-consuming task. This article focuses on providing a novel solution that semiautomatically colorizes a set of images using a single colorized reference image. Our method is able to provide coherent colors for regions that have similar semantics to those in the reference image. An active-learning-based framework is used to match local regions, followed by mixed-integer quadratic programming (MIQP) which considers the spatial contexts to further refine the matching results. We efficiently utilize user interactions to achieve high accuracy in the final colorized images. Experiments show that our method outperforms the current state-of-the-art deep learning based colorization method in terms of color coherency with the reference image. The region matching framework could potentially be applied to other applications, such as color transfer.", "title": "Active Colorization for Cartoon Line Drawings", "normalizedTitle": "Active Colorization for Cartoon Line Drawings", "fno": "09143503", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Image Colour Analysis", "Image Matching", "Integer Programming", "Learning Artificial Intelligence", "Quadratic Programming", "Active Colorization", "Cartoon Line Drawings", "Animation Industry", "Raw Sketch Images", "Single Colorized Reference Image", "Coherent Colors", "Similar Semantics", "Active Learning Based Framework", "Local Regions", "Mixed Integer Quadratic Programming", "Matching Results", "Final Colorized Images", "Current State Of The Art Deep Learning Based Colorization Method", "Color Coherency", "Region Matching Framework", "Color Transfer", "Image Color Analysis", "Image Segmentation", "Semantics", "Feature Extraction", "Shape", "Machine Learning", "Animation", "Active Learning", "Line Drawing Colorization", "Region Matching" ], "authors": [ { "givenName": "Shu-Yu", "surname": "Chen", "fullName": "Shu-Yu Chen", "affiliation": "Beijing Key Laboratory of Mobile Computing and Pervasive Device, Chinese Academy of Sciences, Institute of Computing Technology, Beijing, China", "__typename": "ArticleAuthorType" }, { "givenName": "Jia-Qi", "surname": "Zhang", "fullName": "Jia-Qi Zhang", "affiliation": "University of Chinese Academy of Sciences, Beijing, China", "__typename": "ArticleAuthorType" }, { "givenName": "Lin", "surname": "Gao", "fullName": "Lin Gao", "affiliation": "Beijing Key Laboratory of Mobile Computing and Pervasive Device, Chinese Academy of Sciences, Institute of Computing Technology, Beijing, China", "__typename": "ArticleAuthorType" }, { "givenName": "Yue", "surname": "He", "fullName": "Yue He", "affiliation": "Beijing Key Laboratory of Mobile Computing and Pervasive Device, Chinese Academy of Sciences, Institute of Computing Technology, Beijing, China", "__typename": "ArticleAuthorType" }, { "givenName": "Shihong", "surname": "Xia", "fullName": "Shihong Xia", "affiliation": "Beijing Key Laboratory of Mobile Computing and Pervasive Device, Chinese Academy of Sciences, Institute of Computing Technology, Beijing, China", "__typename": "ArticleAuthorType" }, { "givenName": "Min", "surname": "Shi", "fullName": "Min Shi", "affiliation": "University of Chinese Academy of Sciences, Beijing, China", "__typename": "ArticleAuthorType" }, { "givenName": "Fang-Lue", "surname": "Zhang", "fullName": "Fang-Lue Zhang", "affiliation": "North China Electric Power University, Beijing, China", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "02", "pubDate": "2022-02-01 00:00:00", "pubType": "trans", "pages": "1198-1208", "year": "2022", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, 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{ "issue": { "id": "1zKXryr0JDG", "title": "Feb.", "year": "2022", "issueNum": "02", "idPrefix": "tg", "pubType": "journal", "volume": "28", "label": "Feb.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "1ujXLK9Vgac", "doi": "10.1109/TVCG.2021.3088343", "abstract": "Many metaphors in language reflect conceptual metaphors that structure thought. In line with metaphorical expressions such as &#x2018;high number&#x2019;, experiments show that people associate larger numbers with upward space. Consistent with this metaphor, high numbers are conventionally depicted in high positions on the <inline-formula><tex-math notation=\"LaTeX\">Z_$y$_Z</tex-math></inline-formula>-axis of line graphs. People also associate good and bad (emotional valence) with upward and downward locations, in line with metaphorical expressions such as &#x2018;uplifting&#x2019; and &#x2018;down in the dumps&#x2019;. Graphs depicting good quantities (e.g., vacation days) are consistent with graphical convention and the valence metaphor, because &#x2018;more&#x2019; of the good quantity is represented by higher <inline-formula><tex-math notation=\"LaTeX\">Z_$y$_Z</tex-math></inline-formula>-axis positions. In contrast, graphs depicting bad quantities (e.g., murders) are consistent with graphical convention, but not the valence metaphor, because more of the bad quantity is represented by higher (rather than lower) <inline-formula><tex-math notation=\"LaTeX\">Z_$y$_Z</tex-math></inline-formula>-axis positions. We conducted two experiments (<italic>N</italic> = 300 per experiment) where participants answered questions about line graphs depicting good and bad quantities. For some graphs, we inverted the conventional axis ordering of numbers. Line graphs that aligned (versus misaligned) with valence metaphors (up = good) were easier to interpret, but this beneficial effect did not outweigh the adverse effect of inverting the axis numbering. Line graphs depicting good (versus bad) quantities were easier to interpret, as were graphs that depicted quantity using the <inline-formula><tex-math notation=\"LaTeX\">Z_$x$_Z</tex-math></inline-formula>-axis (versus <inline-formula><tex-math notation=\"LaTeX\">Z_$y$_Z</tex-math></inline-formula>-axis). Our results suggest that conceptual metaphors matter for the interpretation of line graphs. However, designers of line graphs are warned against subverting graphical convention to align with conceptual metaphors.", "abstracts": [ { "abstractType": "Regular", "content": "Many metaphors in language reflect conceptual metaphors that structure thought. In line with metaphorical expressions such as &#x2018;high number&#x2019;, experiments show that people associate larger numbers with upward space. Consistent with this metaphor, high numbers are conventionally depicted in high positions on the <inline-formula><tex-math notation=\"LaTeX\">$y$</tex-math><alternatives><mml:math><mml:mi>y</mml:mi></mml:math><inline-graphic xlink:href=\"woodin-ieq1-3088343.gif\"/></alternatives></inline-formula>-axis of line graphs. People also associate good and bad (emotional valence) with upward and downward locations, in line with metaphorical expressions such as &#x2018;uplifting&#x2019; and &#x2018;down in the dumps&#x2019;. Graphs depicting good quantities (e.g., vacation days) are consistent with graphical convention and the valence metaphor, because &#x2018;more&#x2019; of the good quantity is represented by higher <inline-formula><tex-math notation=\"LaTeX\">$y$</tex-math><alternatives><mml:math><mml:mi>y</mml:mi></mml:math><inline-graphic xlink:href=\"woodin-ieq2-3088343.gif\"/></alternatives></inline-formula>-axis positions. In contrast, graphs depicting bad quantities (e.g., murders) are consistent with graphical convention, but not the valence metaphor, because more of the bad quantity is represented by higher (rather than lower) <inline-formula><tex-math notation=\"LaTeX\">$y$</tex-math><alternatives><mml:math><mml:mi>y</mml:mi></mml:math><inline-graphic xlink:href=\"woodin-ieq3-3088343.gif\"/></alternatives></inline-formula>-axis positions. We conducted two experiments (<italic>N</italic> = 300 per experiment) where participants answered questions about line graphs depicting good and bad quantities. For some graphs, we inverted the conventional axis ordering of numbers. Line graphs that aligned (versus misaligned) with valence metaphors (up = good) were easier to interpret, but this beneficial effect did not outweigh the adverse effect of inverting the axis numbering. Line graphs depicting good (versus bad) quantities were easier to interpret, as were graphs that depicted quantity using the <inline-formula><tex-math notation=\"LaTeX\">$x$</tex-math><alternatives><mml:math><mml:mi>x</mml:mi></mml:math><inline-graphic xlink:href=\"woodin-ieq4-3088343.gif\"/></alternatives></inline-formula>-axis (versus <inline-formula><tex-math notation=\"LaTeX\">$y$</tex-math><alternatives><mml:math><mml:mi>y</mml:mi></mml:math><inline-graphic xlink:href=\"woodin-ieq5-3088343.gif\"/></alternatives></inline-formula>-axis). Our results suggest that conceptual metaphors matter for the interpretation of line graphs. However, designers of line graphs are warned against subverting graphical convention to align with conceptual metaphors.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Many metaphors in language reflect conceptual metaphors that structure thought. In line with metaphorical expressions such as ‘high number’, experiments show that people associate larger numbers with upward space. Consistent with this metaphor, high numbers are conventionally depicted in high positions on the --axis of line graphs. People also associate good and bad (emotional valence) with upward and downward locations, in line with metaphorical expressions such as ‘uplifting’ and ‘down in the dumps’. Graphs depicting good quantities (e.g., vacation days) are consistent with graphical convention and the valence metaphor, because ‘more’ of the good quantity is represented by higher --axis positions. In contrast, graphs depicting bad quantities (e.g., murders) are consistent with graphical convention, but not the valence metaphor, because more of the bad quantity is represented by higher (rather than lower) --axis positions. We conducted two experiments (N = 300 per experiment) where participants answered questions about line graphs depicting good and bad quantities. For some graphs, we inverted the conventional axis ordering of numbers. Line graphs that aligned (versus misaligned) with valence metaphors (up = good) were easier to interpret, but this beneficial effect did not outweigh the adverse effect of inverting the axis numbering. Line graphs depicting good (versus bad) quantities were easier to interpret, as were graphs that depicted quantity using the --axis (versus --axis). Our results suggest that conceptual metaphors matter for the interpretation of line graphs. However, designers of line graphs are warned against subverting graphical convention to align with conceptual metaphors.", "title": "Conceptual Metaphor and Graphical Convention Influence the Interpretation of Line Graphs", "normalizedTitle": "Conceptual Metaphor and Graphical Convention Influence the Interpretation of Line Graphs", "fno": "09451590", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Graph Theory", "Conceptual Metaphor", "Graphical Convention Influence", "Line Graphs", "Metaphorical Expressions", "Valence Metaphor", "Yy Axis Positions", "Emotional Valence", "Data Visualization", "Linguistics", "Cognitive Science", "Visualization", "Psychology", "Market Research", "Random Sequences", "Conceptual Metaphor Theory", "More Is Up", "Mental Number Line", "Cognition", "Linguistics", "Emotional Valence", "Line Graph", "Axis Reversal", "Handedness", "Empirical Evaluation" ], "authors": [ { "givenName": "Greg", "surname": "Woodin", "fullName": "Greg Woodin", "affiliation": "Department of English Language and Linguistics, University of Birmingham, Birmingham, U.K.", "__typename": "ArticleAuthorType" }, { "givenName": "Bodo", "surname": "Winter", "fullName": "Bodo Winter", "affiliation": "Department of English Language and Linguistics, University of Birmingham, Birmingham, U.K.", "__typename": "ArticleAuthorType" }, { "givenName": "Lace", "surname": "Padilla", "fullName": "Lace Padilla", "affiliation": "Spatial Perception, Applied Cognition & Education Lab, University of California Merced, Merced, CA, USA", "__typename": "ArticleAuthorType" } ], "replicability": { "isEnabled": true, "codeDownloadUrl": "https://github.com/GregWoodin/dataviz.git", "codeRepositoryUrl": "https://github.com/GregWoodin/dataviz", "__typename": "ArticleReplicabilityType" }, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "02", "pubDate": "2022-02-01 00:00:00", "pubType": "trans", "pages": "1209-1221", "year": "2022", "issn": "1077-2626", 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{ "issue": { "id": "1zKXryr0JDG", "title": "Feb.", "year": "2022", "issueNum": "02", "idPrefix": "tg", "pubType": "journal", "volume": "28", "label": "Feb.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "1lNXFpGivV6", "doi": "10.1109/TVCG.2020.3012063", "abstract": "Classifiers are among the most widely used supervised machine learning algorithms. Many classification models exist, and choosing the right one for a given task is difficult. During model selection and debugging, data scientists need to assess classifiers&#x0027; performances, evaluate their learning behavior over time, and compare different models. Typically, this analysis is based on single-number performance measures such as accuracy. A more detailed evaluation of classifiers is possible by inspecting class errors. The confusion matrix is an established way for visualizing these class errors, but it was not designed with temporal or comparative analysis in mind. More generally, established performance analysis systems do not allow a combined temporal and comparative analysis of class-level information. To address this issue, we propose ConfusionFlow, an interactive, comparative visualization tool that combines the benefits of class confusion matrices with the visualization of performance characteristics over time. ConfusionFlow is model-agnostic and can be used to compare performances for different model types, model architectures, and/or training and test datasets. We demonstrate the usefulness of ConfusionFlow in a case study on instance selection strategies in active learning. We further assess the scalability of ConfusionFlow and present a use case in the context of neural network pruning.", "abstracts": [ { "abstractType": "Regular", "content": "Classifiers are among the most widely used supervised machine learning algorithms. Many classification models exist, and choosing the right one for a given task is difficult. During model selection and debugging, data scientists need to assess classifiers&#x0027; performances, evaluate their learning behavior over time, and compare different models. Typically, this analysis is based on single-number performance measures such as accuracy. A more detailed evaluation of classifiers is possible by inspecting class errors. The confusion matrix is an established way for visualizing these class errors, but it was not designed with temporal or comparative analysis in mind. More generally, established performance analysis systems do not allow a combined temporal and comparative analysis of class-level information. To address this issue, we propose ConfusionFlow, an interactive, comparative visualization tool that combines the benefits of class confusion matrices with the visualization of performance characteristics over time. ConfusionFlow is model-agnostic and can be used to compare performances for different model types, model architectures, and/or training and test datasets. We demonstrate the usefulness of ConfusionFlow in a case study on instance selection strategies in active learning. We further assess the scalability of ConfusionFlow and present a use case in the context of neural network pruning.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Classifiers are among the most widely used supervised machine learning algorithms. Many classification models exist, and choosing the right one for a given task is difficult. During model selection and debugging, data scientists need to assess classifiers' performances, evaluate their learning behavior over time, and compare different models. Typically, this analysis is based on single-number performance measures such as accuracy. A more detailed evaluation of classifiers is possible by inspecting class errors. The confusion matrix is an established way for visualizing these class errors, but it was not designed with temporal or comparative analysis in mind. More generally, established performance analysis systems do not allow a combined temporal and comparative analysis of class-level information. To address this issue, we propose ConfusionFlow, an interactive, comparative visualization tool that combines the benefits of class confusion matrices with the visualization of performance characteristics over time. ConfusionFlow is model-agnostic and can be used to compare performances for different model types, model architectures, and/or training and test datasets. We demonstrate the usefulness of ConfusionFlow in a case study on instance selection strategies in active learning. We further assess the scalability of ConfusionFlow and present a use case in the context of neural network pruning.", "title": "ConfusionFlow: A Model-Agnostic Visualization for Temporal Analysis of Classifier Confusion", "normalizedTitle": "ConfusionFlow: A Model-Agnostic Visualization for Temporal Analysis of Classifier Confusion", "fno": "09149790", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Data Visualisation", "Feature Selection", "Matrix Algebra", "Neural Nets", "Pattern Classification", "Supervised Learning", "Active Learning", "Confusion Flow", "Model Agnostic Visualization", "Classifier Confusion", "Supervised Machine Learning", "Confusion Matrix", "Temporal Analysis", "Class Level Information", "Class Confusion Matrices", "Performance Characteristics", "Instance Selection Strategies", "Neural Network Pruning", "Task Analysis", "Analytical Models", "Data Models", "Training", "Tools", "Adaptation Models", "Data Visualization", "Classification", "Performance Analysis", "Time Series Visualization", "Machine Learning", "Information Visualization", "Quality Assessment" ], "authors": [ { "givenName": "Andreas", "surname": "Hinterreiter", "fullName": "Andreas Hinterreiter", "affiliation": "Johannes Kepler University Linz, Linz, Austria", "__typename": "ArticleAuthorType" }, { "givenName": "Peter", "surname": "Ruch", "fullName": "Peter Ruch", "affiliation": "Imperial College London, London, United Kingdom", "__typename": "ArticleAuthorType" }, { "givenName": "Holger", "surname": "Stitz", "fullName": "Holger Stitz", "affiliation": "Johannes Kepler University Linz, Linz, Austria", "__typename": "ArticleAuthorType" }, { "givenName": "Martin", "surname": "Ennemoser", "fullName": "Martin Ennemoser", "affiliation": "Johannes Kepler University Linz, Linz, Austria", "__typename": "ArticleAuthorType" }, { "givenName": "Jürgen", "surname": "Bernard", "fullName": "Jürgen Bernard", "affiliation": "Salesbeat GmbH, Leonding, Austria", "__typename": "ArticleAuthorType" }, { "givenName": "Hendrik", "surname": "Strobelt", "fullName": "Hendrik Strobelt", "affiliation": "Datavisyn GmbH, Linz, Austria", "__typename": "ArticleAuthorType" }, { "givenName": "Marc", "surname": "Streit", "fullName": "Marc Streit", "affiliation": "Imperial College London, London, United Kingdom", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "02", "pubDate": "2022-02-01 00:00:00", "pubType": "trans", "pages": "1222-1236", "year": "2022", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/icdar/2013/4999/0/06628769", "title": "Using Confusion Reject to Improve (User and) System (Cross) Learning of Gesture Commands", "doi": null, "abstractUrl": "/proceedings-article/icdar/2013/06628769/12OmNz2TCDY", "parentPublication": { "id": "proceedings/icdar/2013/4999/0", "title": "2013 12th 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and Images (SIBGRAPI)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iccv/2021/2812/0/281200j123", "title": "Robust Object Detection via Instance-Level Temporal Cycle Confusion", "doi": null, "abstractUrl": "/proceedings-article/iccv/2021/281200j123/1BmKhYtYfS0", "parentPublication": { "id": "proceedings/iccv/2021/2812/0", "title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/csde/2021/9552/0/09718422", "title": "Confusion detection using neural networks", "doi": null, "abstractUrl": "/proceedings-article/csde/2021/09718422/1BogXApz88U", "parentPublication": { "id": "proceedings/csde/2021/9552/0", "title": "2021 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/ta/5555/01/09786857", 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{ "issue": { "id": "1zKXryr0JDG", "title": "Feb.", "year": "2022", "issueNum": "02", "idPrefix": "tg", "pubType": "journal", "volume": "28", "label": "Feb.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "1y11cQpf9nO", "doi": "10.1109/TVCG.2021.3122388", "abstract": "Embedding high-dimensional data onto a low-dimensional manifold is of both theoretical and practical value. In this article, we propose to combine deep neural networks (DNN) with mathematics-guided embedding rules for high-dimensional data embedding. We introduce a generic deep embedding network (DEN) framework, which is able to learn a parametric mapping from high-dimensional space to low-dimensional space, guided by well-established objectives such as Kullback-Leibler (KL) divergence minimization. We further propose a recursive strategy, called deep recursive embedding (DRE), to make use of the latent data representations for boosted embedding performance. We exemplify the flexibility of DRE by different architectures and loss functions, and benchmarked our method against the two most popular embedding methods, namely, t-distributed stochastic neighbor embedding (t-SNE) and uniform manifold approximation and projection (UMAP). The proposed DRE method can map out-of-sample data and scale to extremely large datasets. Experiments on a range of public datasets demonstrated improved embedding performance in terms of local and global structure preservation, compared with other state-of-the-art embedding methods. Code is available at <uri>https://github.com/tao-aimi/DeepRecursiveEmbedding</uri>.", "abstracts": [ { "abstractType": "Regular", "content": "Embedding high-dimensional data onto a low-dimensional manifold is of both theoretical and practical value. In this article, we propose to combine deep neural networks (DNN) with mathematics-guided embedding rules for high-dimensional data embedding. We introduce a generic deep embedding network (DEN) framework, which is able to learn a parametric mapping from high-dimensional space to low-dimensional space, guided by well-established objectives such as Kullback-Leibler (KL) divergence minimization. We further propose a recursive strategy, called deep recursive embedding (DRE), to make use of the latent data representations for boosted embedding performance. We exemplify the flexibility of DRE by different architectures and loss functions, and benchmarked our method against the two most popular embedding methods, namely, t-distributed stochastic neighbor embedding (t-SNE) and uniform manifold approximation and projection (UMAP). The proposed DRE method can map out-of-sample data and scale to extremely large datasets. Experiments on a range of public datasets demonstrated improved embedding performance in terms of local and global structure preservation, compared with other state-of-the-art embedding methods. Code is available at <uri>https://github.com/tao-aimi/DeepRecursiveEmbedding</uri>.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Embedding high-dimensional data onto a low-dimensional manifold is of both theoretical and practical value. In this article, we propose to combine deep neural networks (DNN) with mathematics-guided embedding rules for high-dimensional data embedding. We introduce a generic deep embedding network (DEN) framework, which is able to learn a parametric mapping from high-dimensional space to low-dimensional space, guided by well-established objectives such as Kullback-Leibler (KL) divergence minimization. We further propose a recursive strategy, called deep recursive embedding (DRE), to make use of the latent data representations for boosted embedding performance. We exemplify the flexibility of DRE by different architectures and loss functions, and benchmarked our method against the two most popular embedding methods, namely, t-distributed stochastic neighbor embedding (t-SNE) and uniform manifold approximation and projection (UMAP). The proposed DRE method can map out-of-sample data and scale to extremely large datasets. Experiments on a range of public datasets demonstrated improved embedding performance in terms of local and global structure preservation, compared with other state-of-the-art embedding methods. Code is available at https://github.com/tao-aimi/DeepRecursiveEmbedding.", "title": "Deep Recursive Embedding for High-Dimensional Data", "normalizedTitle": "Deep Recursive Embedding for High-Dimensional Data", "fno": "09585419", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Data Handling", "Data Structures", "Deep Learning Artificial Intelligence", "Minimisation", "Stochastic Processes", "Uniform Manifold Approximation And Projection", "T Distributed Stochastic Neighbor Embedding", "Generic Deep Embedding Network", "Deep Recursive Embedding", "Out Of Sample Data", "Latent Data Representations", "Kullback Leibler Divergence Minimization", "High Dimensional Data Embedding", "Mathematics Guided Embedding Rules", "Deep Neural Networks", "Data Visualization", "Feature Extraction", "Training", "Manifolds", "Unsupervised Learning", "Standards", "Tools", "T Distributed Stochastic Neighbor Embedding", "Uniform Manifold Approximation And Projection", "Deep Embedding Network", "Deep Recursive Embedding", "Unsupervised Learning" ], "authors": [ { "givenName": "Zixia", "surname": "Zhou", "fullName": "Zixia Zhou", "affiliation": "Department of Electronic Engineering, Fudan University, Shanghai, China", "__typename": "ArticleAuthorType" }, { "givenName": "Xinrui", "surname": "Zu", "fullName": "Xinrui Zu", "affiliation": "Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS), University of Twente, Enschede, NB, The Netherlands", "__typename": "ArticleAuthorType" }, { "givenName": "Yuanyuan", "surname": "Wang", "fullName": "Yuanyuan Wang", "affiliation": "Department of Electronic Engineering, Fudan University, Shanghai, China", "__typename": "ArticleAuthorType" }, { "givenName": "Boudewijn P. F.", "surname": "Lelieveldt", "fullName": "Boudewijn P. F. Lelieveldt", "affiliation": "Department of Radiology, Division of Image Processing, Leiden University Medical Center, Leiden, ZA, The Netherlands", "__typename": "ArticleAuthorType" }, { "givenName": "Qian", "surname": "Tao", "fullName": "Qian Tao", "affiliation": "Department of Imaging Physics, Delft University of Technology, Delft, CJ, The Netherlands", "__typename": "ArticleAuthorType" } ], "replicability": { "isEnabled": true, "codeDownloadUrl": "https://github.com/tao-aimi/DeepRecursiveEmbedding.git", "codeRepositoryUrl": "https://github.com/tao-aimi/DeepRecursiveEmbedding", "__typename": "ArticleReplicabilityType" }, "showBuyMe": false, "showRecommendedArticles": true, "isOpenAccess": true, "issueNum": "02", "pubDate": "2022-02-01 00:00:00", "pubType": "trans", "pages": "1237-1248", "year": "2022", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/icdmw/2016/5910/0/07836739", "title": 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{ "issue": { "id": "1zKXryr0JDG", "title": "Feb.", "year": "2022", "issueNum": "02", "idPrefix": "tg", "pubType": "journal", "volume": "28", "label": "Feb.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "1hN4BrDSVHi", "doi": "10.1109/TVCG.2020.2976986", "abstract": "The goal of Mixed Reality (MR) is to achieve a seamless and realistic blending between real and virtual worlds. This requires the estimation of reflectance properties and lighting characteristics of the real scene. One of the main challenges within this task consists in recovering such properties using a single RGB-D camera. In this article, we introduce a novel framework to recover both the position and color of multiple light sources as well as the specular reflectance of real scene surfaces. This is achieved by detecting and incorporating information from both specular reflections and cast shadows. Our approach is capable of handling any textured surface and considers both static and dynamic light sources. Its effectiveness is demonstrated through a range of applications including visually-consistent mixed reality scenarios (e.g., correct real specularity removal, coherent shadows in terms of shape and intensity) and retexturing where the texture of the scene is altered whereas the incident lighting is preserved.", "abstracts": [ { "abstractType": "Regular", "content": "The goal of Mixed Reality (MR) is to achieve a seamless and realistic blending between real and virtual worlds. This requires the estimation of reflectance properties and lighting characteristics of the real scene. One of the main challenges within this task consists in recovering such properties using a single RGB-D camera. In this article, we introduce a novel framework to recover both the position and color of multiple light sources as well as the specular reflectance of real scene surfaces. This is achieved by detecting and incorporating information from both specular reflections and cast shadows. Our approach is capable of handling any textured surface and considers both static and dynamic light sources. Its effectiveness is demonstrated through a range of applications including visually-consistent mixed reality scenarios (e.g., correct real specularity removal, coherent shadows in terms of shape and intensity) and retexturing where the texture of the scene is altered whereas the incident lighting is preserved.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "The goal of Mixed Reality (MR) is to achieve a seamless and realistic blending between real and virtual worlds. This requires the estimation of reflectance properties and lighting characteristics of the real scene. One of the main challenges within this task consists in recovering such properties using a single RGB-D camera. In this article, we introduce a novel framework to recover both the position and color of multiple light sources as well as the specular reflectance of real scene surfaces. This is achieved by detecting and incorporating information from both specular reflections and cast shadows. Our approach is capable of handling any textured surface and considers both static and dynamic light sources. Its effectiveness is demonstrated through a range of applications including visually-consistent mixed reality scenarios (e.g., correct real specularity removal, coherent shadows in terms of shape and intensity) and retexturing where the texture of the scene is altered whereas the incident lighting is preserved.", "title": "Detecting Specular Reflections and Cast Shadows to Estimate Reflectance and Illumination of Dynamic Indoor Scenes", "normalizedTitle": "Detecting Specular Reflections and Cast Shadows to Estimate Reflectance and Illumination of Dynamic Indoor Scenes", "fno": "09018202", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Cameras", "Image Colour Analysis", "Image Texture", "Lighting", "Object Detection", "Virtual Reality", "Specular Reflections", "Cast Shadows", "Dynamic Indoor Scenes", "Seamless Blending", "Realistic Blending", "Reflectance Properties", "Lighting Characteristics", "Single RGB D Camera", "Multiple Light Sources", "Specular Reflectance", "Scene Surfaces", "Detecting Incorporating Information", "Static Sources", "Dynamic Light Sources", "Visually Consistent Mixed Reality Scenarios", "Correct Real Specularity Removal", "Lighting", "Light Sources", "Virtual Reality", "Three Dimensional Displays", "Cameras", "Image Color Analysis", "Surface Texture", "Photometric Registration", "Illumination", "Reflectance", "Diffuse", "Specular", "Shadow", "Texture", "Mixed Reality", "Retexturing" ], "authors": [ { "givenName": "Salma", "surname": "Jiddi", "fullName": "Salma Jiddi", "affiliation": "Geomagical Labs, Mountain View, CA, USA", "__typename": "ArticleAuthorType" }, { "givenName": "Philippe", "surname": "Robert", "fullName": "Philippe Robert", "affiliation": "Interdigital, Rennes, France", "__typename": "ArticleAuthorType" }, { "givenName": "Eric", "surname": "Marchand", "fullName": "Eric Marchand", "affiliation": "CNRS, IRISA, Univ Rennes, Inria, Rennes, France", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, 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"ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/cvprw/2012/1611/0/06239343", "title": "Recovering spectral reflectance under commonly available lighting conditions", "doi": null, "abstractUrl": "/proceedings-article/cvprw/2012/06239343/12OmNBTs7yq", "parentPublication": { "id": "proceedings/cvprw/2012/1611/0", "title": "2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iccv/1999/0164/2/00790314", "title": "Illumination distribution from brightness in shadows: Adaptive estimation of illumination distribution with unknown reflectance properties in shadow regions", "doi": null, "abstractUrl": "/proceedings-article/iccv/1999/00790314/12OmNvAiSCT", "parentPublication": { "id": "proceedings/iccv/1999/0164/2", "title": "Proceedings of the Seventh IEEE International Conference on Computer Vision", "__typename": 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CVPR 2004.", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iccv/2009/4420/0/05459381", "title": "Attached shadow coding: Estimating surface normals from shadows under unknown reflectance and lighting conditions", "doi": null, "abstractUrl": "/proceedings-article/iccv/2009/05459381/12OmNylsZWO", "parentPublication": { "id": "proceedings/iccv/2009/4420/0", "title": "2009 IEEE 12th International Conference on Computer Vision (ICCV)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tp/2020/07/09064908", "title": "Shape and Reflectance Reconstruction Using Concentric Multi-Spectral Light Field", "doi": null, "abstractUrl": "/journal/tp/2020/07/09064908/1iZGtGUiMhO", "parentPublication": { "id": "trans/tp", "title": "IEEE Transactions on Pattern Analysis & Machine Intelligence", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "09585419", "articleId": "1y11cQpf9nO", "__typename": "AdjacentArticleType" }, "next": { "fno": "09144483", "articleId": "1lClltCZfOg", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [], "articleVideos": [] }
{ "issue": { "id": "1zKXryr0JDG", "title": "Feb.", "year": "2022", "issueNum": "02", "idPrefix": "tg", "pubType": "journal", "volume": "28", "label": "Feb.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "1lClltCZfOg", "doi": "10.1109/TVCG.2020.3010247", "abstract": "As a hyper-natural interaction technique in 3D user interfaces, non-isomorphic rotation has been considered an effective approach for rotation tasks, where a static or dynamic control-display gain can be applied to amplify or attenuate a rotation. However, it is not clear whether non-isomorphic rotation can benefit 6-degree-of-freedom (6-DOF) manipulation tasks in AR and VR. In this article, we extended the usability studies of non-isomorphic rotation from rotation-only tasks to 6-DOF manipulation tasks and analyzed the collected data using a 2-component model. Using a mixed reality (MR) simulation approach, we also investigated whether environment (AR or VR) had an impact on 3D manipulation tasks. The results reveal that although both static and dynamic non-isomorphic rotation techniques could save time and effort in ballistic phases, only dynamic non-isomorphic rotation was significantly faster than isomorphic rotation. Interestingly, while environment had no significant impact on overall user performance, we found evidence that it could affect fine-tuning in correction phases. We also found that most participants preferred AR over VR, indicating that environmental visual realism could be helpful to improve user experience.", "abstracts": [ { "abstractType": "Regular", "content": "As a hyper-natural interaction technique in 3D user interfaces, non-isomorphic rotation has been considered an effective approach for rotation tasks, where a static or dynamic control-display gain can be applied to amplify or attenuate a rotation. However, it is not clear whether non-isomorphic rotation can benefit 6-degree-of-freedom (6-DOF) manipulation tasks in AR and VR. In this article, we extended the usability studies of non-isomorphic rotation from rotation-only tasks to 6-DOF manipulation tasks and analyzed the collected data using a 2-component model. Using a mixed reality (MR) simulation approach, we also investigated whether environment (AR or VR) had an impact on 3D manipulation tasks. The results reveal that although both static and dynamic non-isomorphic rotation techniques could save time and effort in ballistic phases, only dynamic non-isomorphic rotation was significantly faster than isomorphic rotation. Interestingly, while environment had no significant impact on overall user performance, we found evidence that it could affect fine-tuning in correction phases. We also found that most participants preferred AR over VR, indicating that environmental visual realism could be helpful to improve user experience.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "As a hyper-natural interaction technique in 3D user interfaces, non-isomorphic rotation has been considered an effective approach for rotation tasks, where a static or dynamic control-display gain can be applied to amplify or attenuate a rotation. However, it is not clear whether non-isomorphic rotation can benefit 6-degree-of-freedom (6-DOF) manipulation tasks in AR and VR. In this article, we extended the usability studies of non-isomorphic rotation from rotation-only tasks to 6-DOF manipulation tasks and analyzed the collected data using a 2-component model. Using a mixed reality (MR) simulation approach, we also investigated whether environment (AR or VR) had an impact on 3D manipulation tasks. The results reveal that although both static and dynamic non-isomorphic rotation techniques could save time and effort in ballistic phases, only dynamic non-isomorphic rotation was significantly faster than isomorphic rotation. Interestingly, while environment had no significant impact on overall user performance, we found evidence that it could affect fine-tuning in correction phases. We also found that most participants preferred AR over VR, indicating that environmental visual realism could be helpful to improve user experience.", "title": "Evaluating the Effects of Non-Isomorphic Rotation on 3D Manipulation Tasks in Mixed Reality Simulation", "normalizedTitle": "Evaluating the Effects of Non-Isomorphic Rotation on 3D Manipulation Tasks in Mixed Reality Simulation", "fno": "09144483", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Augmented Reality", "Computer Displays", "Data Visualisation", "Ergonomics", "Graphical User Interfaces", "Human Computer Interaction", "Human Factors", "Interactive Systems", "Touch Sensitive Screens", "Rotation Tasks", "Nonisomorphic Rotation Techniques", "Isomorphic Rotation", "3 D User Interfaces", "Hyper Natural Interaction Technique", "Mixed Reality Simulation", "Task Analysis", "Three Dimensional Displays", "Virtual Reality", "Solid Modeling", "User Interfaces", "Usability", "Manipulator Dynamics", "Virtual Reality", "Augmented Reality", "Mixed Reality Simulation", "3 D Interaction", "Non Isomorphic Rotation" ], "authors": [ { "givenName": "Zihan", "surname": "Gao", "fullName": "Zihan Gao", "affiliation": "College of Computer Science and Technology, Harbin Engineering University, Harbin, Heilongjiang, China", "__typename": "ArticleAuthorType" }, { "givenName": "Huiqiang", "surname": "Wang", "fullName": "Huiqiang Wang", "affiliation": "College of Computer Science and Technology, Harbin Engineering University, Harbin, Heilongjiang, China", "__typename": "ArticleAuthorType" }, { "givenName": "Hongwu", "surname": "Lv", "fullName": "Hongwu Lv", "affiliation": "College of Computer Science and Technology, Harbin Engineering University, Harbin, Heilongjiang, China", "__typename": "ArticleAuthorType" }, { "givenName": "Moshu", "surname": "Wang", "fullName": "Moshu Wang", "affiliation": "College of Computer Science and Technology, Harbin Engineering University, Harbin, Heilongjiang, China", "__typename": "ArticleAuthorType" }, { "givenName": "Yifan", "surname": "Qi", "fullName": "Yifan Qi", "affiliation": "Peng Cheng Laboratory, Shenzhen, Guangdong, China", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "02", "pubDate": "2022-02-01 00:00:00", "pubType": "trans", "pages": "1261-1273", "year": "2022", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/3dui/2007/0907/0/04142845", "title": "An Exploration of Non-Isomorphic 3D Rotation in Surround Screen Virtual Environments", "doi": null, "abstractUrl": "/proceedings-article/3dui/2007/04142845/12OmNAJ4pea", "parentPublication": { "id": "proceedings/3dui/2007/0907/0", "title": "2007 IEEE Symposium on 3D User Interfaces", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iv/1999/0210/0/02100032", "title": "Virtual Reality and Augmented Reality as a Training Tool for Assembly Tasks", "doi": null, "abstractUrl": "/proceedings-article/iv/1999/02100032/12OmNAObbyR", "parentPublication": { "id": "proceedings/iv/1999/0210/0", "title": "1999 IEEE International Conference on Information Visualization (Cat. No. PR00210)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/3dui/2008/2047/0/04476614", "title": "Poster: Effects of Head Tracking and Stereo on Non-Isomorphic 3D Rotation", "doi": null, "abstractUrl": "/proceedings-article/3dui/2008/04476614/12OmNqEAT7R", "parentPublication": { "id": "proceedings/3dui/2008/2047/0", "title": "2008 IEEE Symposium on 3D User Interfaces", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2018/02/07833028", "title": "Augmented Reality versus Virtual Reality for 3D Object Manipulation", "doi": null, "abstractUrl": "/journal/tg/2018/02/07833028/13rRUwInvsX", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vrw/2022/8402/0/840200a620", "title": "Design of Mentally and Physically Demanding Tasks as Distractors of Rotation Gains", "doi": null, "abstractUrl": "/proceedings-article/vrw/2022/840200a620/1CJdavNhwAw", "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/vrw/2022/8402/0/840200a538", "title": "Effects of Clutching Mechanism on Remote Object Manipulation Tasks", "doi": null, "abstractUrl": "/proceedings-article/vrw/2022/840200a538/1CJf9GYjHMc", "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/2022/11/09874255", "title": "Precueing Object Placement and Orientation for Manual Tasks in Augmented Reality", "doi": null, "abstractUrl": "/journal/tg/2022/11/09874255/1GjwLnkmt8I", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/imet/2022/7016/0/09929500", "title": "Interactive Historical Documentary in Virtual Reality", "doi": null, "abstractUrl": "/proceedings-article/imet/2022/09929500/1HYuTheBVYY", "parentPublication": { "id": "proceedings/imet/2022/7016/0", "title": "2022 International Conference on Interactive Media, Smart Systems and Emerging Technologies (IMET)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vrw/2020/6532/0/09090415", "title": "Enhancing Proxy-Based Haptics in Virtual Reality", "doi": null, "abstractUrl": "/proceedings-article/vrw/2020/09090415/1jIxtWMak6c", "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/vr/2021/1838/0/255600a778", "title": "Evaluating Object Manipulation Interaction Techniques in Mixed Reality: Tangible User Interfaces and Gesture", "doi": null, "abstractUrl": "/proceedings-article/vr/2021/255600a778/1tuBngWRAC4", "parentPublication": { "id": "proceedings/vr/2021/1838/0", "title": "2021 IEEE Virtual Reality and 3D User Interfaces (VR)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "09018202", "articleId": "1hN4BrDSVHi", "__typename": "AdjacentArticleType" }, "next": { "fno": "09157962", "articleId": "1m1eKuAoOoE", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [], "articleVideos": [] }
{ "issue": { "id": "1zKXryr0JDG", "title": "Feb.", "year": "2022", "issueNum": "02", "idPrefix": "tg", "pubType": "journal", "volume": "28", "label": "Feb.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "1m1eKuAoOoE", "doi": "10.1109/TVCG.2020.3013876", "abstract": "Facial expression retargeting from humans to virtual characters is a useful technique in computer graphics and animation. Traditional methods use markers or blendshapes to construct a mapping between the human and avatar faces. However, these approaches require a tedious 3D modeling process, and the performance relies on the modelers&#x2019; experience. In this article, we propose a brand-new solution to this cross-domain expression transfer problem via nonlinear expression embedding and expression domain translation. We first build low-dimensional latent spaces for the human and avatar facial expressions with variational autoencoder. Then we construct correspondences between the two latent spaces guided by geometric and perceptual constraints. Specifically, we design geometric correspondences to reflect geometric matching and utilize a triplet data structure to express users&#x2019; perceptual preference of avatar expressions. A user-friendly method is proposed to automatically generate triplets for a system allowing users to easily and efficiently annotate the correspondences. Using both geometric and perceptual correspondences, we trained a network for expression domain translation from human to avatar. Extensive experimental results and user studies demonstrate that even nonprofessional users can apply our method to generate high-quality facial expression retargeting results with less time and effort.", "abstracts": [ { "abstractType": "Regular", "content": "Facial expression retargeting from humans to virtual characters is a useful technique in computer graphics and animation. Traditional methods use markers or blendshapes to construct a mapping between the human and avatar faces. However, these approaches require a tedious 3D modeling process, and the performance relies on the modelers&#x2019; experience. In this article, we propose a brand-new solution to this cross-domain expression transfer problem via nonlinear expression embedding and expression domain translation. We first build low-dimensional latent spaces for the human and avatar facial expressions with variational autoencoder. Then we construct correspondences between the two latent spaces guided by geometric and perceptual constraints. Specifically, we design geometric correspondences to reflect geometric matching and utilize a triplet data structure to express users&#x2019; perceptual preference of avatar expressions. A user-friendly method is proposed to automatically generate triplets for a system allowing users to easily and efficiently annotate the correspondences. Using both geometric and perceptual correspondences, we trained a network for expression domain translation from human to avatar. Extensive experimental results and user studies demonstrate that even nonprofessional users can apply our method to generate high-quality facial expression retargeting results with less time and effort.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Facial expression retargeting from humans to virtual characters is a useful technique in computer graphics and animation. Traditional methods use markers or blendshapes to construct a mapping between the human and avatar faces. However, these approaches require a tedious 3D modeling process, and the performance relies on the modelers’ experience. In this article, we propose a brand-new solution to this cross-domain expression transfer problem via nonlinear expression embedding and expression domain translation. We first build low-dimensional latent spaces for the human and avatar facial expressions with variational autoencoder. Then we construct correspondences between the two latent spaces guided by geometric and perceptual constraints. Specifically, we design geometric correspondences to reflect geometric matching and utilize a triplet data structure to express users’ perceptual preference of avatar expressions. A user-friendly method is proposed to automatically generate triplets for a system allowing users to easily and efficiently annotate the correspondences. Using both geometric and perceptual correspondences, we trained a network for expression domain translation from human to avatar. Extensive experimental results and user studies demonstrate that even nonprofessional users can apply our method to generate high-quality facial expression retargeting results with less time and effort.", "title": "Facial Expression Retargeting From Human to Avatar Made Easy", "normalizedTitle": "Facial Expression Retargeting From Human to Avatar Made Easy", "fno": "09157962", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Avatars", "Computer Animation", "Data Structures", "Face Recognition", "Learning Artificial Intelligence", "Video Signal Processing", "Expression Domain Translation", "Low Dimensional Latent Spaces", "Human Expressions", "Avatar Facial Expressions", "Geometric Constraints", "Perceptual Constraints", "Design Geometric Correspondences", "Users", "Avatar Expressions", "User Friendly Method", "Perceptual Correspondences", "High Quality Facial Expression", "Facial Expression Retargeting", "Avatar Made Easy", "Human Faces", "Avatar Faces", "Tedious 3 D Modeling Process", "Modelers", "Cross Domain Expression Transfer Problem", "Nonlinear Expression Embedding", "Avatars", "Three Dimensional Displays", "Strain", "Animation", "Shape", "Solid Modeling", "Machine Learning", "Facial Expression Retargeting", "Variational Autoencoder", "Deformation Transfer", "Cross Domain Translation", "Triplet" ], "authors": [ { "givenName": "Juyong", "surname": "Zhang", "fullName": "Juyong Zhang", "affiliation": "School of Mathematical Sciences, University of Science and Technology of China, Hefei, Anhui, China", "__typename": "ArticleAuthorType" }, { "givenName": "Keyu", "surname": "Chen", "fullName": "Keyu Chen", "affiliation": "School of Mathematical Sciences, University of Science and Technology of China, Hefei, Anhui, China", "__typename": "ArticleAuthorType" }, { "givenName": "Jianmin", "surname": "Zheng", "fullName": "Jianmin Zheng", "affiliation": "School of Computer Science and Engineering, Nanyang Technological University, Singapore", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "02", "pubDate": "2022-02-01 00:00:00", "pubType": "trans", "pages": "1274-1287", "year": "2022", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/fg/2011/9140/0/05771364", "title": "Facial expression recognition using emotion avatar image", "doi": null, "abstractUrl": "/proceedings-article/fg/2011/05771364/12OmNAi6vUx", "parentPublication": { "id": "proceedings/fg/2011/9140/0", "title": "Face and Gesture 2011", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/fg/2011/9140/0/05771400", "title": "Real-time avatar animation from a single image", "doi": null, "abstractUrl": "/proceedings-article/fg/2011/05771400/12OmNButpYT", "parentPublication": { "id": "proceedings/fg/2011/9140/0", "title": "Face and Gesture 2011", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icmu/2015/2612/0/07061027", "title": "Development of avatar creation smartphone application reflecting expression of Japanese comics character", "doi": null, "abstractUrl": "/proceedings-article/icmu/2015/07061027/12OmNyvY9zW", "parentPublication": { "id": "proceedings/icmu/2015/2612/0", "title": "2015 Eighth International Conference on Mobile Computing and Ubiquitous Networking (ICMU)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2016/11/07523447", "title": "Retargeting Human-Object Interaction to Virtual Avatars", "doi": null, "abstractUrl": "/journal/tg/2016/11/07523447/13rRUzp02ot", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/cvpr/2022/6946/0/694600n3535", "title": "I M Avatar: Implicit Morphable Head Avatars from Videos", "doi": null, "abstractUrl": "/proceedings-article/cvpr/2022/694600n3535/1H1j2BWBE2c", "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/vr/2019/1377/0/08798353", "title": "Rapid 3D Avatar Creation System Using a Single Depth Camera", "doi": null, "abstractUrl": "/proceedings-article/vr/2019/08798353/1cJ11TRykmY", "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/iccvw/2019/5023/0/502300c100", "title": "Landmark-Guided Deformation Transfer of Template Facial Expressions for Automatic Generation of Avatar Blendshapes", "doi": null, "abstractUrl": "/proceedings-article/iccvw/2019/502300c100/1i5mNnnOzlu", "parentPublication": { "id": "proceedings/iccvw/2019/5023/0", "title": "2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tp/2022/11/09507281", "title": "Detailed Avatar Recovery From Single Image", "doi": null, "abstractUrl": "/journal/tp/2022/11/09507281/1vNfwmj8UCY", "parentPublication": { "id": "trans/tp", "title": "IEEE Transactions on Pattern Analysis & Machine Intelligence", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/compsac/2021/2463/0/246300b036", "title": "How Do Avatar Appearances Affect Communication from Others?", "doi": null, "abstractUrl": "/proceedings-article/compsac/2021/246300b036/1wLcE9cNine", "parentPublication": { "id": "proceedings/compsac/2021/2463/0", "title": "2021 IEEE 45th Annual Computers, Software, and Applications Conference (COMPSAC)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/ismar/2021/0158/0/015800a128", "title": "AlterEcho: Loose Avatar-Streamer Coupling for Expressive VTubing", "doi": null, "abstractUrl": "/proceedings-article/ismar/2021/015800a128/1yeCWKEosp2", "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": "09144483", "articleId": "1lClltCZfOg", "__typename": "AdjacentArticleType" }, "next": { "fno": "09165928", "articleId": "1mevWoz3hM4", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [ { "id": "1zKXwKPDIeQ", "name": "ttg202202-09157962s1-supp1-3013876.mp4", "location": "https://www.computer.org/csdl/api/v1/extra/ttg202202-09157962s1-supp1-3013876.mp4", 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{ "issue": { "id": "1zKXryr0JDG", "title": "Feb.", "year": "2022", "issueNum": "02", "idPrefix": "tg", "pubType": "journal", "volume": "28", "label": "Feb.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "1mevWoz3hM4", "doi": "10.1109/TVCG.2020.3016055", "abstract": "Many real-world networks are globally sparse but locally dense. Typical examples are social networks, biological networks, and information networks. This double structural nature makes it difficult to adopt a homogeneous visualization model that clearly conveys both an overview of the network and the internal structure of its communities at the same time. As a consequence, the use of hybrid visualizations has been proposed. For instance, <sc>NodeTrix</sc> combines node-link and matrix-based representations (Henry <italic>et al.</italic>, 2007). In this article we describe <sc>ChordLink</sc>, a hybrid visualization model that embeds chord diagrams, used to represent dense subgraphs, into a node-link diagram, which shows the global network structure. The visualization makes it possible to interactively highlight the structure of a community while keeping the rest of the layout stable. We discuss the intriguing algorithmic challenges behind the <sc>ChordLink</sc> model, present a prototype system that implements it, and illustrate case studies on real-world networks.", "abstracts": [ { "abstractType": "Regular", "content": "Many real-world networks are globally sparse but locally dense. Typical examples are social networks, biological networks, and information networks. This double structural nature makes it difficult to adopt a homogeneous visualization model that clearly conveys both an overview of the network and the internal structure of its communities at the same time. As a consequence, the use of hybrid visualizations has been proposed. For instance, <sc>NodeTrix</sc> combines node-link and matrix-based representations (Henry <italic>et al.</italic>, 2007). In this article we describe <sc>ChordLink</sc>, a hybrid visualization model that embeds chord diagrams, used to represent dense subgraphs, into a node-link diagram, which shows the global network structure. The visualization makes it possible to interactively highlight the structure of a community while keeping the rest of the layout stable. We discuss the intriguing algorithmic challenges behind the <sc>ChordLink</sc> model, present a prototype system that implements it, and illustrate case studies on real-world networks.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Many real-world networks are globally sparse but locally dense. Typical examples are social networks, biological networks, and information networks. This double structural nature makes it difficult to adopt a homogeneous visualization model that clearly conveys both an overview of the network and the internal structure of its communities at the same time. As a consequence, the use of hybrid visualizations has been proposed. For instance, NodeTrix combines node-link and matrix-based representations (Henry et al., 2007). In this article we describe ChordLink, a hybrid visualization model that embeds chord diagrams, used to represent dense subgraphs, into a node-link diagram, which shows the global network structure. The visualization makes it possible to interactively highlight the structure of a community while keeping the rest of the layout stable. We discuss the intriguing algorithmic challenges behind the ChordLink model, present a prototype system that implements it, and illustrate case studies on real-world networks.", "title": "Hybrid Graph Visualizations With ChordLink: Algorithms, Experiments, and Applications", "normalizedTitle": "Hybrid Graph Visualizations With ChordLink: Algorithms, Experiments, and Applications", "fno": "09165928", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Data Visualisation", "Graph Theory", "Social Networking Online", "Real World Networks", "Typical Examples", "Social Networks", "Biological Networks", "Information Networks", "Double Structural Nature", "Homogeneous Visualization Model", "Internal Structure", "Hybrid Visualizations", "Matrix Based Representations", "Hybrid Visualization Model", "Chord Diagrams", "Dense Subgraphs", "Node Link Diagram", "Global Network Structure", "Intriguing Algorithmic Challenges", "Chord Link Model", "Hybrid Graph Visualizations", "Visualization", "Layout", "Task Analysis", "Semiconductor Device Modeling", "Prototypes", "Sparse Matrices", "Stability Analysis", "Network Visualization", "Graph Drawing", "Hybrid Visualization", "Chord Diagrams", "Optimization Algorithms", "Systems" ], "authors": [ { "givenName": "Lorenzo", "surname": "Angori", "fullName": "Lorenzo Angori", "affiliation": "Dipartimento di Ingegneria, Università degli Studi di Perugia, Perugia, Italy", "__typename": "ArticleAuthorType" }, { "givenName": "Walter", "surname": "Didimo", "fullName": "Walter Didimo", "affiliation": "Dipartimento di Ingegneria, Università degli Studi di Perugia, Perugia, Italy", "__typename": "ArticleAuthorType" }, { "givenName": "Fabrizio", "surname": "Montecchiani", "fullName": "Fabrizio Montecchiani", "affiliation": "Dipartimento di Ingegneria, Università degli Studi di Perugia, Perugia, Italy", "__typename": "ArticleAuthorType" }, { "givenName": "Daniele", "surname": "Pagliuca", "fullName": "Daniele Pagliuca", "affiliation": "Agenzia delle Entrate, Arezzo, Italy", "__typename": "ArticleAuthorType" }, { "givenName": "Alessandra", "surname": "Tappini", "fullName": "Alessandra Tappini", "affiliation": "Dipartimento di Ingegneria, Università degli Studi di Perugia, Perugia, Italy", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "02", "pubDate": "2022-02-01 00:00:00", "pubType": "trans", "pages": "1288-1300", "year": "2022", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/aiccsa/2017/3581/0/3581a033", "title": "Performance Evaluation for Dense Sparse Matrix Product Algorithms", "doi": null, "abstractUrl": "/proceedings-article/aiccsa/2017/3581a033/12OmNBQC86U", "parentPublication": { "id": "proceedings/aiccsa/2017/3581/0", "title": "2017 IEEE/ACS 14th International Conference on Computer Systems and Applications (AICCSA)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "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/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/5555/01/10004748", "title": "Comparative Study and Evaluation of Hybrid Visualizations of Graphs", "doi": null, "abstractUrl": "/journal/tg/5555/01/10004748/1JC5xZN3afu", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/td/5555/01/10086668", "title": "Sparse Symmetric Format for Tucker Decomposition", "doi": null, "abstractUrl": "/journal/td/5555/01/10086668/1LUpIEoEkgg", "parentPublication": { "id": "trans/td", "title": "IEEE Transactions on Parallel & Distributed Systems", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "mags/cg/2021/02/09238399", "title": "<sc>Cartolabe</sc>: A Web-Based Scalable Visualization of Large Document Collections", "doi": null, "abstractUrl": "/magazine/cg/2021/02/09238399/1oa1KJAPKOA", "parentPublication": { "id": "mags/cg", "title": "IEEE Computer Graphics and Applications", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": 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{ "issue": { "id": "1zKXryr0JDG", "title": "Feb.", "year": "2022", "issueNum": "02", "idPrefix": "tg", "pubType": "journal", "volume": "28", "label": "Feb.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "1lE0csLCf6g", "doi": "10.1109/TVCG.2020.3010694", "abstract": "We present a system to extract architectural assets from large-scale collections of panoramic imagery. We automatically rectify and crop parts of the panoramic image that contain dominant planes, and then use object detection to extract assets such as fa&#x00E7;ades and windows. We also provide various tools to identify attributes of the assets to determine the asset quality and index the assets for search. In addition, we propose a User Interface (UI) to visualize and query assets. Finally, we present applications for urban modeling and texture synthesis.", "abstracts": [ { "abstractType": "Regular", "content": "We present a system to extract architectural assets from large-scale collections of panoramic imagery. We automatically rectify and crop parts of the panoramic image that contain dominant planes, and then use object detection to extract assets such as fa&#x00E7;ades and windows. We also provide various tools to identify attributes of the assets to determine the asset quality and index the assets for search. In addition, we propose a User Interface (UI) to visualize and query assets. Finally, we present applications for urban modeling and texture synthesis.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "We present a system to extract architectural assets from large-scale collections of panoramic imagery. We automatically rectify and crop parts of the panoramic image that contain dominant planes, and then use object detection to extract assets such as façades and windows. We also provide various tools to identify attributes of the assets to determine the asset quality and index the assets for search. In addition, we propose a User Interface (UI) to visualize and query assets. Finally, we present applications for urban modeling and texture synthesis.", "title": "Large-Scale Architectural Asset Extraction from Panoramic Imagery", "normalizedTitle": "Large-Scale Architectural Asset Extraction from Panoramic Imagery", "fno": "09145640", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Architecture", "Data Visualisation", "Feature Extraction", "Image Texture", "Query Processing", "User Interfaces", "Panoramic Imagery", "Asset Quality", "Large Scale Architectural Asset Extraction", "Object Detection", "User Interface", "Asset Visualization", "Asset Query", "Urban Modeling", "Texture Synthesis", "Panoramic Image Cropping", "Fac X 0327 Ades", "Windows", "Data Mining", "Object Detection", "Solid Modeling", "Urban Planning", "Microsoft Windows", "Visualization", "Three Dimensional Displays", "Asset Extraction", "Urban Modeling", "Object Detection", "Clustering", "Semantic Segmentation" ], "authors": [ { "givenName": "Peihao", "surname": "Zhu", "fullName": "Peihao Zhu", "affiliation": "Department of Computer Science, King Abdullah University of Science and Technology, Thuwal, Jeddah, Saudi Arabia", "__typename": "ArticleAuthorType" }, { "givenName": "Wamiq Reyaz", "surname": "Para", "fullName": "Wamiq Reyaz Para", "affiliation": "Department of Computer Science, King Abdullah University of Science and Technology, Thuwal, Jeddah, Saudi Arabia", "__typename": "ArticleAuthorType" }, { "givenName": "Anna", "surname": "Frühstück", "fullName": "Anna Frühstück", "affiliation": "Department of Computer Science, King Abdullah University of Science and Technology, Thuwal, Jeddah, Saudi Arabia", "__typename": "ArticleAuthorType" }, { "givenName": "John", "surname": "Femiani", "fullName": "John Femiani", "affiliation": "College of Engineering and Computing, Miami University, Oxford, Ohio, USA", "__typename": "ArticleAuthorType" }, { "givenName": "Peter", "surname": "Wonka", "fullName": "Peter Wonka", "affiliation": "Department of Computer Science, King Abdullah University of Science and Technology, Thuwal, Jeddah, Saudi Arabia", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "02", "pubDate": "2022-02-01 00:00:00", "pubType": "trans", "pages": "1301-1316", "year": "2022", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/icpr/2006/2521/3/01699692", "title": "Extraction of trabecular structures of mandible excluding tooth roots on dental panoramic radiographs using mathematical morphology", "doi": null, "abstractUrl": "/proceedings-article/icpr/2006/01699692/12OmNBK5m8j", "parentPublication": { "id": "proceedings/icpr/2006/2521/3", "title": "2006 18th International Conference on Pattern Recognition", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/cvpr/2004/2158/2/01315152", "title": "Extraction and integration of window in a 3D building model from ground view images", "doi": null, "abstractUrl": "/proceedings-article/cvpr/2004/01315152/12OmNBV9Igj", "parentPublication": { "id": "proceedings/cvpr/2004/2158/2", "title": "Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004.", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/cvprw/2010/7029/0/05543519", "title": "Estimating Gothic facade architecture from imagery", "doi": null, "abstractUrl": "/proceedings-article/cvprw/2010/05543519/12OmNyY4rgF", "parentPublication": { "id": "proceedings/cvprw/2010/7029/0", "title": "2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iccvw/2009/4442/0/05457501", "title": "Region extraction in large-scale urban LIDAR data", "doi": null, "abstractUrl": "/proceedings-article/iccvw/2009/05457501/12OmNya72qU", "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/dmdcm/2011/4413/0/4413a066", "title": "Towards 3D City Modeling through Combining Ground Level Panoramic and Orthogonal Aerial Imagery", "doi": null, "abstractUrl": "/proceedings-article/dmdcm/2011/4413a066/12OmNzTYBOH", "parentPublication": { "id": "proceedings/dmdcm/2011/4413/0", "title": "Digital Media and Digital Content Management, Workshop on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tp/2019/09/08417901", "title": "A Kronecker Product Model for Repeated Pattern Detection on 2D Urban Images", "doi": null, "abstractUrl": "/journal/tp/2019/09/08417901/13rRUygT7as", "parentPublication": { "id": "trans/tp", "title": "IEEE Transactions on Pattern Analysis & Machine Intelligence", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/acpr/2017/3354/0/3354a162", "title": "Text and Symbol Extraction in Traffic Panel from Natural Scene Images", "doi": null, "abstractUrl": "/proceedings-article/acpr/2017/3354a162/17D45XwUAJ6", "parentPublication": { "id": "proceedings/acpr/2017/3354/0", "title": "2017 4th IAPR Asian Conference on Pattern Recognition (ACPR)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/wacv/2022/0915/0/091500b496", "title": "Lane-Level Street Map Extraction from Aerial Imagery", "doi": null, "abstractUrl": "/proceedings-article/wacv/2022/091500b496/1B13p51QtsQ", "parentPublication": { "id": "proceedings/wacv/2022/0915/0", "title": "2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/cw/2022/6814/0/681400a063", "title": "A Semantics-aware Method for Adding 3D Window Details to Textured LoD2 CityGML Models", "doi": null, "abstractUrl": "/proceedings-article/cw/2022/681400a063/1I6RPcjsVBm", "parentPublication": { "id": "proceedings/cw/2022/6814/0", "title": "2022 International Conference on Cyberworlds (CW)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/itme/2022/1015/0/101500a662", "title": "SFR-Net:A Spatial Feature Enhance Method for Road Extraction", "doi": null, "abstractUrl": "/proceedings-article/itme/2022/101500a662/1M4rB2NfiYo", "parentPublication": { "id": "proceedings/itme/2022/1015/0", "title": "2022 12th International Conference on Information Technology in Medicine and Education (ITME)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "09165928", "articleId": "1mevWoz3hM4", "__typename": "AdjacentArticleType" }, "next": { "fno": "09159927", "articleId": "1m3m77L2v3a", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [ { "id": "1zKXu20hHFK", "name": "ttg202202-09145640s1-supp1-3010694.pdf", "location": "https://www.computer.org/csdl/api/v1/extra/ttg202202-09145640s1-supp1-3010694.pdf", "extension": "pdf", "size": "6.44 MB", "__typename": "WebExtraType" } ], "articleVideos": [] }
{ "issue": { "id": "1zKXryr0JDG", "title": "Feb.", "year": "2022", "issueNum": "02", "idPrefix": "tg", "pubType": "journal", "volume": "28", "label": "Feb.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "1m3m77L2v3a", "doi": "10.1109/TVCG.2020.3014449", "abstract": "3D models are commonly used in computer vision and graphics. With the wider availability of mesh data, an efficient and intrinsic deep learning approach to processing 3D meshes is in great need. Unlike images, 3D meshes have irregular connectivity, requiring careful design to capture relations in the data. To utilize the topology information while staying robust under different triangulations, we propose to encode mesh connectivity using Laplacian spectral analysis, along with mesh feature aggregation blocks (MFABs) that can split the surface domain into local pooling patches and aggregate global information amongst them. We build a mesh hierarchy from fine to coarse using Laplacian spectral clustering, which is flexible under isometric transformations. Inside the MFABs there are pooling layers to collect local information and multi-layer perceptrons to compute vertex features of increasing complexity. To obtain the relationships among different clusters, we introduce a Correlation Net to compute a correlation matrix, which can aggregate the features globally by matrix multiplication with cluster features. Our network architecture is flexible enough to be used on meshes with different numbers of vertices. We conduct several experiments including shape segmentation and classification, and our method outperforms state-of-the-art algorithms for these tasks on the ShapeNet and COSEG datasets.", "abstracts": [ { "abstractType": "Regular", "content": "3D models are commonly used in computer vision and graphics. With the wider availability of mesh data, an efficient and intrinsic deep learning approach to processing 3D meshes is in great need. Unlike images, 3D meshes have irregular connectivity, requiring careful design to capture relations in the data. To utilize the topology information while staying robust under different triangulations, we propose to encode mesh connectivity using Laplacian spectral analysis, along with mesh feature aggregation blocks (MFABs) that can split the surface domain into local pooling patches and aggregate global information amongst them. We build a mesh hierarchy from fine to coarse using Laplacian spectral clustering, which is flexible under isometric transformations. Inside the MFABs there are pooling layers to collect local information and multi-layer perceptrons to compute vertex features of increasing complexity. To obtain the relationships among different clusters, we introduce a Correlation Net to compute a correlation matrix, which can aggregate the features globally by matrix multiplication with cluster features. Our network architecture is flexible enough to be used on meshes with different numbers of vertices. We conduct several experiments including shape segmentation and classification, and our method outperforms state-of-the-art algorithms for these tasks on the ShapeNet and COSEG datasets.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "3D models are commonly used in computer vision and graphics. With the wider availability of mesh data, an efficient and intrinsic deep learning approach to processing 3D meshes is in great need. Unlike images, 3D meshes have irregular connectivity, requiring careful design to capture relations in the data. To utilize the topology information while staying robust under different triangulations, we propose to encode mesh connectivity using Laplacian spectral analysis, along with mesh feature aggregation blocks (MFABs) that can split the surface domain into local pooling patches and aggregate global information amongst them. We build a mesh hierarchy from fine to coarse using Laplacian spectral clustering, which is flexible under isometric transformations. Inside the MFABs there are pooling layers to collect local information and multi-layer perceptrons to compute vertex features of increasing complexity. To obtain the relationships among different clusters, we introduce a Correlation Net to compute a correlation matrix, which can aggregate the features globally by matrix multiplication with cluster features. Our network architecture is flexible enough to be used on meshes with different numbers of vertices. We conduct several experiments including shape segmentation and classification, and our method outperforms state-of-the-art algorithms for these tasks on the ShapeNet and COSEG datasets.", "title": "Learning on 3D Meshes With Laplacian Encoding and Pooling", "normalizedTitle": "Learning on 3D Meshes With Laplacian Encoding and Pooling", "fno": "09159927", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Belief Networks", "Computational Geometry", "Computer Graphics", "Computer Vision", "Feature Extraction", "Graph Theory", "Image Coding", "Image Recognition", "Image Representation", "Image Segmentation", "Learning Artificial Intelligence", "Mesh Generation", "Multilayer Perceptrons", "Object Recognition", "Pattern Clustering", "Solid Modelling", "Spectral Analysis", "Cluster Features", "Computer Vision", "Wider Availability", "Mesh Data", "Efficient Learning Approach", "Intrinsic Deep Learning Approach", "Irregular Connectivity", "Topology Information", "Different Triangulations", "Mesh Connectivity", "Laplacian Spectral Analysis", "Mesh Feature Aggregation Blocks", "MFA Bs", "Local Pooling Patches", "Aggregate Global Information", "Mesh Hierarchy", "Coarse Using Laplacian Spectral Clustering", "Local Information", "Vertex Features", "Three Dimensional Displays", "Laplace Equations", "Shape", "Correlation", "Machine Learning", "Topology", "Computational Modeling", "Mesh Processing", "Segmentation", "Laplacian", "Deep Learning" ], "authors": [ { "givenName": "Yi-Ling", "surname": "Qiao", "fullName": "Yi-Ling Qiao", "affiliation": "Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China", "__typename": "ArticleAuthorType" }, { "givenName": "Lin", "surname": "Gao", "fullName": "Lin Gao", "affiliation": "Department of Computer Science, University of Maryland, College Park, MD, USA", "__typename": "ArticleAuthorType" }, { "givenName": "Jie", "surname": "Yang", "fullName": "Jie Yang", "affiliation": "Department of Computer Science, University of Maryland, College Park, MD, USA", "__typename": "ArticleAuthorType" }, { "givenName": "Paul L.", "surname": "Rosin", "fullName": "Paul L. Rosin", "affiliation": "Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China", "__typename": "ArticleAuthorType" }, { "givenName": "Yu-Kun", "surname": "Lai", "fullName": "Yu-Kun Lai", "affiliation": "Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China", "__typename": "ArticleAuthorType" }, { "givenName": "Xilin", "surname": "Chen", "fullName": "Xilin Chen", "affiliation": "University of Chinese Academy of Sciences, Beijing, China", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "02", "pubDate": "2022-02-01 00:00:00", "pubType": "trans", "pages": "1317-1327", "year": "2022", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": 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"/proceedings-article/cw/2014/4677a130/12OmNzayNus", "parentPublication": { "id": "proceedings/cw/2014/4677/0", "title": "2014 International Conference on Cyberworlds (CW)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tp/2016/01/07110605", "title": "Template-Based Monocular 3D Shape Recovery Using Laplacian Meshes", "doi": null, "abstractUrl": "/journal/tp/2016/01/07110605/13rRUxAASXt", "parentPublication": { "id": "trans/tp", "title": "IEEE Transactions on Pattern Analysis & Machine Intelligence", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2015/05/07006805", "title": "On Linear Spaces of Polyhedral Meshes", "doi": null, "abstractUrl": "/journal/tg/2015/05/07006805/13rRUxYIMV0", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": 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null, "abstractUrl": "/journal/tg/5555/01/10076837/1LFQ6yTQbIs", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/5555/01/10068322", "title": "Efficient Pooling Operator for 3D Morphable Models", "doi": null, "abstractUrl": "/journal/tg/5555/01/10068322/1LtR6T3cY0w", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/cvprw/2020/9360/0/09150750", "title": "Mesh Variational Autoencoders with Edge Contraction Pooling", "doi": null, "abstractUrl": "/proceedings-article/cvprw/2020/09150750/1lPH7Uy2hqw", "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": "09145640", "articleId": "1lE0csLCf6g", "__typename": "AdjacentArticleType" }, "next": { "fno": "09166766", "articleId": "1mgaO3cO3aU", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [], "articleVideos": [] }
{ "issue": { "id": "1zKXryr0JDG", "title": "Feb.", "year": "2022", "issueNum": "02", "idPrefix": "tg", "pubType": "journal", "volume": "28", "label": "Feb.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "1mgaO3cO3aU", "doi": "10.1109/TVCG.2020.3016588", "abstract": "The analysis of vector fields is crucial for the understanding of several physical phenomena, such as natural events (e.g., analysis of waves), diffusive processes, electric and electromagnetic fields. While previous work has been focused mainly on the analysis of 2D or 3D vector fields on volumes or surfaces, we address the meshless analysis of a vector field defined on an arbitrary domain, without assumptions on its dimension and discretisation. The meshless approximation of the Helmholtz-Hodge decomposition of a vector field is achieved by expressing the potential of its components as a linear combination of radial basis functions and by computing the corresponding conservative, irrotational, and harmonic components as solution to a least-squares or to a differential problem. To this end, we identify the conditions on the kernel of the radial basis functions that guarantee the existence of their derivatives. Finally, we demonstrate our approach on 2D and 3D vector fields measured by sensors or generated through simulation.", "abstracts": [ { "abstractType": "Regular", "content": "The analysis of vector fields is crucial for the understanding of several physical phenomena, such as natural events (e.g., analysis of waves), diffusive processes, electric and electromagnetic fields. While previous work has been focused mainly on the analysis of 2D or 3D vector fields on volumes or surfaces, we address the meshless analysis of a vector field defined on an arbitrary domain, without assumptions on its dimension and discretisation. The meshless approximation of the Helmholtz-Hodge decomposition of a vector field is achieved by expressing the potential of its components as a linear combination of radial basis functions and by computing the corresponding conservative, irrotational, and harmonic components as solution to a least-squares or to a differential problem. To this end, we identify the conditions on the kernel of the radial basis functions that guarantee the existence of their derivatives. Finally, we demonstrate our approach on 2D and 3D vector fields measured by sensors or generated through simulation.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "The analysis of vector fields is crucial for the understanding of several physical phenomena, such as natural events (e.g., analysis of waves), diffusive processes, electric and electromagnetic fields. While previous work has been focused mainly on the analysis of 2D or 3D vector fields on volumes or surfaces, we address the meshless analysis of a vector field defined on an arbitrary domain, without assumptions on its dimension and discretisation. The meshless approximation of the Helmholtz-Hodge decomposition of a vector field is achieved by expressing the potential of its components as a linear combination of radial basis functions and by computing the corresponding conservative, irrotational, and harmonic components as solution to a least-squares or to a differential problem. To this end, we identify the conditions on the kernel of the radial basis functions that guarantee the existence of their derivatives. Finally, we demonstrate our approach on 2D and 3D vector fields measured by sensors or generated through simulation.", "title": "Meshless Approximation and Helmholtz-Hodge Decomposition of Vector Fields", "normalizedTitle": "Meshless Approximation and Helmholtz-Hodge Decomposition of Vector Fields", "fno": "09166766", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Electromagnetic Fields", "Helmholtz Equations", "Least Squares Approximations", "Radial Basis Function Networks", "Vectors", "Meshless Approximation", "Helmholtz Hodge Decomposition", "Vector Field", "Electric Fields", "Electromagnetic Fields", "Meshless Analysis", "Arbitrary Domain", "Kernel", "Two Dimensional Displays", "Three Dimensional Displays", "Harmonic Analysis", "Rotors", "Boundary Conditions", "Principal Component Analysis", "Vector Fields", "Helmholtz Hodge Decomposition", "Meshless Representations", "Radial Basis Functions" ], "authors": [ { "givenName": "Giuseppe", "surname": "Patané", "fullName": "Giuseppe Patané", "affiliation": "CNR-IMATI, Consiglio Nazionale delle Ricerche, Istituto di Matematica Applicata e Tecnologie Informatiche Genova, Genova, Italy", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": false, "showRecommendedArticles": true, "isOpenAccess": true, "issueNum": "02", "pubDate": "2022-02-01 00:00:00", "pubType": "trans", "pages": "1-14", "year": "2022", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/cso/2010/6812/1/05532933", "title": "Meshless Virtual Boundary Least-Square Collocation Method for 2-D Elastic Problems", "doi": null, "abstractUrl": "/proceedings-article/cso/2010/05532933/12OmNC3FGjm", "parentPublication": { "id": "proceedings/cso/2010/6812/1", "title": "2010 Third International Joint Conference on Computational Science and Optimization", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icmew/2014/4717/0/06890546", "title": "Feature extraction of complex ocean flow field using the helmholtz-hodge decomposition", "doi": null, "abstractUrl": "/proceedings-article/icmew/2014/06890546/12OmNxA3YZS", "parentPublication": { "id": "proceedings/icmew/2014/4717/0", "title": "2014 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/dsc/2016/1192/0/1192a456", "title": "Topology Analysis of Vector Fields and Application Prospect", "doi": null, "abstractUrl": "/proceedings-article/dsc/2016/1192a456/12OmNxGja5R", "parentPublication": { "id": "proceedings/dsc/2016/1192/0", "title": "2016 IEEE First International Conference on Data Science in Cyberspace (DSC)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "mags/cs/2013/05/mcs2013050042", "title": "Discrete Hodge Theory on Graphs: A Tutorial", "doi": null, "abstractUrl": "/magazine/cs/2013/05/mcs2013050042/13rRUILLkzl", "parentPublication": { "id": "mags/cs", "title": "Computing in Science & Engineering", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2010/02/ttg2010020338", "title": "Meshless Helmholtz-Hodge Decomposition", "doi": null, "abstractUrl": "/journal/tg/2010/02/ttg2010020338/13rRUwI5TXw", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2013/08/ttg2013081386", "title": "The Helmholtz-Hodge Decomposition—A Survey", "doi": null, "abstractUrl": "/journal/tg/2013/08/ttg2013081386/13rRUwI5U7X", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2014/11/06774477", "title": "The Natural Helmholtz-Hodge Decomposition for Open-Boundary Flow Analysis", "doi": null, "abstractUrl": "/journal/tg/2014/11/06774477/13rRUxYrbUJ", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2006/03/v0289", "title": "Segmentation of Discrete Vector Fields", "doi": null, "abstractUrl": "/journal/tg/2006/03/v0289/13rRUxcbnCj", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2013/03/ttg2013030527", "title": "Comments on the \"Meshless Helmholtz-Hodge Decomposition\"", "doi": null, "abstractUrl": "/journal/tg/2013/03/ttg2013030527/13rRUyYSWsU", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/sibgrapi/2018/9264/0/926400a337", "title": "Inverse Projection of Vector Fields", "doi": null, "abstractUrl": "/proceedings-article/sibgrapi/2018/926400a337/17D45XeKgmH", "parentPublication": { "id": "proceedings/sibgrapi/2018/9264/0", "title": "2018 31st SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "09159927", "articleId": "1m3m77L2v3a", "__typename": "AdjacentArticleType" }, "next": { "fno": "09555238", "articleId": "1xjQWgERshq", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [], "articleVideos": [] }
{ "issue": { "id": "1zKXryr0JDG", "title": "Feb.", "year": "2022", "issueNum": "02", "idPrefix": "tg", "pubType": "journal", "volume": "28", "label": "Feb.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "1xjQWgERshq", "doi": "10.1109/TVCG.2021.3116673", "abstract": "Augmented reality applications allow users to enrich their real surroundings with additional digital content. However, due to the limited field of view of augmented reality devices, it can sometimes be difficult to become aware of newly emerging information inside or outside the field of view. Typical visual conflicts like clutter and occlusion of augmentations occur and can be further aggravated especially in the context of dense information spaces. In this article, we evaluate how multisensory cue combinations can improve the awareness for moving out-of-view objects in narrow field of view augmented reality displays. We distinguish between proximity and transition cues in either visual, auditory or tactile manner. Proximity cues are intended to enhance spatial awareness of approaching out-of-view objects while transition cues inform the user that the object just entered the field of view. In study 1, user preference was determined for 6 different cue combinations via forced-choice decisions. In study 2, the 3 most preferred modes were then evaluated with respect to performance and awareness measures in a divided attention reaction task. Both studies were conducted under varying noise levels. We show that on average the Visual-Tactile combination leads to 63&#x0025; and Audio-Tactile to 65&#x0025; faster reactions to incoming out-of-view augmentations than their Visual-Audio counterpart, indicating a high usefulness of tactile transition cues. We further show a detrimental effect of visual and audio noise on performance when feedback included visual proximity cues. Based on these results, we make recommendations to determine which cue combination is appropriate for which application.", "abstracts": [ { "abstractType": "Regular", "content": "Augmented reality applications allow users to enrich their real surroundings with additional digital content. However, due to the limited field of view of augmented reality devices, it can sometimes be difficult to become aware of newly emerging information inside or outside the field of view. Typical visual conflicts like clutter and occlusion of augmentations occur and can be further aggravated especially in the context of dense information spaces. In this article, we evaluate how multisensory cue combinations can improve the awareness for moving out-of-view objects in narrow field of view augmented reality displays. We distinguish between proximity and transition cues in either visual, auditory or tactile manner. Proximity cues are intended to enhance spatial awareness of approaching out-of-view objects while transition cues inform the user that the object just entered the field of view. In study 1, user preference was determined for 6 different cue combinations via forced-choice decisions. In study 2, the 3 most preferred modes were then evaluated with respect to performance and awareness measures in a divided attention reaction task. Both studies were conducted under varying noise levels. We show that on average the Visual-Tactile combination leads to 63&#x0025; and Audio-Tactile to 65&#x0025; faster reactions to incoming out-of-view augmentations than their Visual-Audio counterpart, indicating a high usefulness of tactile transition cues. We further show a detrimental effect of visual and audio noise on performance when feedback included visual proximity cues. Based on these results, we make recommendations to determine which cue combination is appropriate for which application.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Augmented reality applications allow users to enrich their real surroundings with additional digital content. However, due to the limited field of view of augmented reality devices, it can sometimes be difficult to become aware of newly emerging information inside or outside the field of view. Typical visual conflicts like clutter and occlusion of augmentations occur and can be further aggravated especially in the context of dense information spaces. In this article, we evaluate how multisensory cue combinations can improve the awareness for moving out-of-view objects in narrow field of view augmented reality displays. We distinguish between proximity and transition cues in either visual, auditory or tactile manner. Proximity cues are intended to enhance spatial awareness of approaching out-of-view objects while transition cues inform the user that the object just entered the field of view. In study 1, user preference was determined for 6 different cue combinations via forced-choice decisions. In study 2, the 3 most preferred modes were then evaluated with respect to performance and awareness measures in a divided attention reaction task. Both studies were conducted under varying noise levels. We show that on average the Visual-Tactile combination leads to 63% and Audio-Tactile to 65% faster reactions to incoming out-of-view augmentations than their Visual-Audio counterpart, indicating a high usefulness of tactile transition cues. We further show a detrimental effect of visual and audio noise on performance when feedback included visual proximity cues. Based on these results, we make recommendations to determine which cue combination is appropriate for which application.", "title": "Multisensory Proximity and Transition Cues for Improving Target Awareness in Narrow Field of View Augmented Reality Displays", "normalizedTitle": "Multisensory Proximity and Transition Cues for Improving Target Awareness in Narrow Field of View Augmented Reality Displays", "fno": "09555238", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Augmented Reality", "Data Visualisation", "Multisensory Proximity", "Target Awareness", "Augmented Reality Applications", "Digital Content", "Augmented Reality Devices", "Visual Conflicts", "Augmentations Occur", "Dense Information Spaces", "Cue Combination", "Out Of View Objects", "Reality Displays", "Visual Manner", "Auditory Manner", "Tactile Manner", "Spatial Awareness", "User Preference", "Cue Combinations", "Awareness Measures", "Visual Tactile Combination", "Out Of View Augmentations", "Visual Audio Counterpart", "Tactile Transition Cues", "Visual Noise", "Audio Noise", "Visual Proximity Cues", "Visualization", "Task Analysis", "Three Dimensional Displays", "Augmented Reality", "Urban Areas", "Working Environment Noise", "Search Problems", "Augmented Reality", "View Management", "Guidance", "Multisensory Cues", "Performance", "Situation Awareness" ], "authors": [ { "givenName": "Christina", "surname": "Trepkowski", "fullName": "Christina Trepkowski", "affiliation": "Bonn-Rhein-Sieg University of Applied Sciences, Sankt Augustin, Germany", "__typename": "ArticleAuthorType" }, { "givenName": "Alexander", "surname": "Marquardt", "fullName": "Alexander Marquardt", "affiliation": "Bonn-Rhein-Sieg University of Applied Sciences, Sankt Augustin, Germany", "__typename": "ArticleAuthorType" }, { "givenName": "Tom David", "surname": "Eibich", "fullName": "Tom David Eibich", "affiliation": "Bonn-Rhein-Sieg University of Applied Sciences, Sankt Augustin, Germany", "__typename": "ArticleAuthorType" }, { "givenName": "Yusuke", "surname": "Shikanai", "fullName": "Yusuke Shikanai", "affiliation": "Nara Institute of Science and Technology, Ikoma, Nara, Japan", "__typename": "ArticleAuthorType" }, { "givenName": "Jens", "surname": "Maiero", "fullName": "Jens Maiero", "affiliation": "Bonn-Rhein-Sieg University of Applied Sciences, Sankt Augustin, Germany", "__typename": "ArticleAuthorType" }, { "givenName": "Kiyoshi", "surname": "Kiyokawa", "fullName": "Kiyoshi Kiyokawa", "affiliation": "Nara Institute of Science and Technology, Ikoma, Nara, Japan", "__typename": "ArticleAuthorType" }, { "givenName": "Ernst", "surname": "Kruijff", "fullName": "Ernst Kruijff", "affiliation": "Bonn-Rhein-Sieg University of Applied Sciences, Sankt Augustin, Germany", "__typename": "ArticleAuthorType" }, { "givenName": "Johannes", "surname": "Schöning", "fullName": "Johannes Schöning", "affiliation": "University of St. Gallen, St. Gallen, Switzerland", "__typename": "ArticleAuthorType" }, { "givenName": "Peter", "surname": "König", "fullName": "Peter König", "affiliation": "Osnabrück University, Osnabrück, Germany", "__typename": "ArticleAuthorType" } ], "replicability": { "isEnabled": true, "codeDownloadUrl": "https://github.com/amarqu88/Multisensory-Proximity-and-Transition-Cues.git", "codeRepositoryUrl": "https://github.com/amarqu88/Multisensory-Proximity-and-Transition-Cues", "__typename": "ArticleReplicabilityType" }, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "02", "pubDate": "2022-02-01 00:00:00", "pubType": "trans", "pages": "1342-1362", "year": "2022", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/vr/2017/6647/0/07892274", "title": "Mechanism of integrating force and vibrotactile cues for 3D user interaction within virtual environments", "doi": null, "abstractUrl": "/proceedings-article/vr/2017/07892274/12OmNqH9hid", "parentPublication": { "id": "proceedings/vr/2017/6647/0", "title": "2017 IEEE Virtual Reality (VR)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icme/2014/4761/0/06890148", "title": "Using mid-high level cues to detect salient object", "doi": null, "abstractUrl": "/proceedings-article/icme/2014/06890148/12OmNvT2oJR", "parentPublication": { "id": "proceedings/icme/2014/4761/0", "title": "2014 IEEE International Conference on Multimedia and Expo (ICME)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/ismar/2013/2869/0/06671795", "title": "Study of augmented gesture communication cues and view sharing in remote collaboration", "doi": null, "abstractUrl": "/proceedings-article/ismar/2013/06671795/12OmNwl8GBu", "parentPublication": { "id": "proceedings/ismar/2013/2869/0", "title": "2013 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2018/11/08493594", "title": "A Comparison of Predictive Spatial Augmented Reality Cues for Procedural Tasks", "doi": null, "abstractUrl": "/journal/tg/2018/11/08493594/14M3DYV3qyA", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vr/2019/1377/0/08797991", "title": "Position Paper: Factors of Perceived Tactile Cue Dominance when Interacting with Moving Virtual Objects", "doi": null, "abstractUrl": "/proceedings-article/vr/2019/08797991/1cJ1aAfvipO", "parentPublication": { "id": "proceedings/vr/2019/1377/0", "title": "2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2019/11/08799015", "title": "Conveying spatial awareness cues in xR collaborations", "doi": null, "abstractUrl": "/journal/tg/2019/11/08799015/1cumXlkNGuY", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/ismar/2019/0987/0/08943620", "title": "Non-Visual Cues for View Management in Narrow Field of View Augmented Reality Displays", "doi": null, "abstractUrl": "/proceedings-article/ismar/2019/08943620/1grOLej5Rh6", "parentPublication": { "id": "proceedings/ismar/2019/0987/0", "title": "2019 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/ismar-adjunct/2019/4765/0/476500a340", "title": "Less is More: Using Spatialized Auditory and Visual Cues for Target Acquisition in a Real-World Search Task", "doi": null, "abstractUrl": "/proceedings-article/ismar-adjunct/2019/476500a340/1gysnlmPxzq", "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/2020/12/09199570", "title": "Comparing Non-Visual and Visual Guidance Methods for Narrow Field of View Augmented Reality Displays", "doi": null, "abstractUrl": "/journal/tg/2020/12/09199570/1ncgoC1SEMw", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/ismar-adjunct/2021/1298/0/129800a159", "title": "Exploring the Effect of Visual Cues on Eye Gaze During AR-Guided Picking and Assembly Tasks", "doi": null, "abstractUrl": "/proceedings-article/ismar-adjunct/2021/129800a159/1yeQM18rD7G", 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{ "issue": { "id": "1zKXryr0JDG", "title": "Feb.", "year": "2022", "issueNum": "02", "idPrefix": "tg", "pubType": "journal", "volume": "28", "label": "Feb.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "1lPCq0H8hUY", "doi": "10.1109/TVCG.2020.3012288", "abstract": "Computing the Voronoi diagram of a given set of points in a restricted domain (e.g., inside a 2D polygon, on a 3D surface, or within a volume) has many applications. Although existing algorithms can compute 2D and surface Voronoi diagrams in parallel on graphics hardware, computing clipped Voronoi diagrams within volumes remains a challenge. This article proposes an efficient GPU algorithm to tackle this problem. A preprocessing step discretizes the input volume into a tetrahedral mesh. Then, unlike existing approaches which use the bisecting planes of the Voronoi cells to clip the tetrahedra, we use the four planes of each tetrahedron to clip the Voronoi cells. This strategy drastically simplifies the computation, and as a result, it outperforms state-of-the-art CPU methods up to an order of magnitude.", "abstracts": [ { "abstractType": "Regular", "content": "Computing the Voronoi diagram of a given set of points in a restricted domain (e.g., inside a 2D polygon, on a 3D surface, or within a volume) has many applications. Although existing algorithms can compute 2D and surface Voronoi diagrams in parallel on graphics hardware, computing clipped Voronoi diagrams within volumes remains a challenge. This article proposes an efficient GPU algorithm to tackle this problem. A preprocessing step discretizes the input volume into a tetrahedral mesh. Then, unlike existing approaches which use the bisecting planes of the Voronoi cells to clip the tetrahedra, we use the four planes of each tetrahedron to clip the Voronoi cells. This strategy drastically simplifies the computation, and as a result, it outperforms state-of-the-art CPU methods up to an order of magnitude.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Computing the Voronoi diagram of a given set of points in a restricted domain (e.g., inside a 2D polygon, on a 3D surface, or within a volume) has many applications. Although existing algorithms can compute 2D and surface Voronoi diagrams in parallel on graphics hardware, computing clipped Voronoi diagrams within volumes remains a challenge. This article proposes an efficient GPU algorithm to tackle this problem. A preprocessing step discretizes the input volume into a tetrahedral mesh. Then, unlike existing approaches which use the bisecting planes of the Voronoi cells to clip the tetrahedra, we use the four planes of each tetrahedron to clip the Voronoi cells. This strategy drastically simplifies the computation, and as a result, it outperforms state-of-the-art CPU methods up to an order of magnitude.", "title": "Parallel Computation of 3D Clipped Voronoi Diagrams", "normalizedTitle": "Parallel Computation of 3D Clipped Voronoi Diagrams", "fno": "09151267", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Computational Geometry", "Graphics Processing Units", "Solid Modelling", "Parallel Computation", "GPU", "Voronoi Cells", "3 D Clipped Voronoi Diagrams", "Tetrahedral Mesh", "Three Dimensional Displays", "Graphics Processing Units", "Heuristic Algorithms", "Two Dimensional Displays", "Robustness", "Approximation Algorithms", "Euclidean Distance", "Parallel Algorithm", "Voronoi Diagram", "Clipping" ], "authors": [ { "givenName": "Xiaohan", "surname": "Liu", "fullName": "Xiaohan Liu", "affiliation": "National Laboratory of Pattern Recognition (NLPR), Chinese Academy of Sciences (CASIA), Institute of Automation, Beijing, China", "__typename": "ArticleAuthorType" }, { "givenName": "Lei", "surname": "Ma", "fullName": "Lei Ma", "affiliation": "School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China", "__typename": "ArticleAuthorType" }, { "givenName": "Jianwei", "surname": "Guo", "fullName": "Jianwei Guo", "affiliation": "National Laboratory of Pattern Recognition (NLPR), Chinese Academy of Sciences (CASIA), Institute of Automation, Beijing, China", "__typename": "ArticleAuthorType" }, { "givenName": "Dong-Ming", "surname": "Yan", "fullName": "Dong-Ming Yan", "affiliation": "National Engineering Laboratory for Video Technology, Peking University, Beijing, China", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "02", "pubDate": "2022-02-01 00:00:00", "pubType": "trans", "pages": "1363-1372", "year": "2022", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/isvd/2009/3781/0/3781a144", "title": "An Algorithm for Computing Voronoi Diagrams of General Generators in General Normed Spaces", "doi": null, "abstractUrl": "/proceedings-article/isvd/2009/3781a144/12OmNqzcvLc", "parentPublication": { "id": "proceedings/isvd/2009/3781/0", "title": "2009 Sixth International Symposium on Voronoi Diagrams", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icmtma/2015/7143/0/7143a006", "title": "A Faster Algorithm of Higher Order Voronoi Diagrams", "doi": null, "abstractUrl": "/proceedings-article/icmtma/2015/7143a006/12OmNvHoQr7", "parentPublication": { "id": "proceedings/icmtma/2015/7143/0", "title": "2015 Seventh International Conference on Measuring Technology and Mechatronics Automation (ICMTMA)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/cgi/1997/7825/0/78250230", "title": "Geodesic Voronoi Diagrams on Parametric Surfaces", "doi": null, "abstractUrl": "/proceedings-article/cgi/1997/78250230/12OmNwDACyS", "parentPublication": { "id": "proceedings/cgi/1997/7825/0", "title": "Computer Graphics International Conference", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/isvd/2010/4112/0/4112a171", "title": "Maximal Zone Diagrams and their Computation", "doi": null, "abstractUrl": "/proceedings-article/isvd/2010/4112a171/12OmNwtEELR", "parentPublication": { "id": "proceedings/isvd/2010/4112/0", "title": "2010 International Symposium on Voronoi Diagrams in Science and Engineering", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/isvd/2013/5037/0/5037a047", "title": "Voronoi Diagrams from (Possibly Discontinuous) Embeddings", "doi": null, "abstractUrl": "/proceedings-article/isvd/2013/5037a047/12OmNyQGSnr", "parentPublication": { "id": "proceedings/isvd/2013/5037/0", "title": "2013 10th International Symposium on Voronoi Diagrams in Science and Engineering (ISVD)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/isvd/2009/3781/0/3781a031", "title": "Voronoi Diagrams and Polynomial Root-Finding", "doi": null, "abstractUrl": "/proceedings-article/isvd/2009/3781a031/12OmNyRxFzq", "parentPublication": { "id": "proceedings/isvd/2009/3781/0", "title": "2009 Sixth International Symposium on Voronoi Diagrams", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/isvd/2010/4112/0/4112a013", "title": "Planar Voronoi Diagrams for Sums of Convex Functions, Smoothed Distance and Dilation", "doi": null, "abstractUrl": "/proceedings-article/isvd/2010/4112a013/12OmNzn38N2", "parentPublication": { "id": "proceedings/isvd/2010/4112/0", "title": "2010 International Symposium on Voronoi Diagrams in Science and Engineering", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "mags/cg/1995/02/mcg1995020052", "title": "Voronoi Diagrams for Planar Shapes", "doi": null, "abstractUrl": "/magazine/cg/1995/02/mcg1995020052/13rRUxZRbr6", "parentPublication": { "id": "mags/cg", "title": "IEEE Computer Graphics and Applications", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tp/1998/07/i0757", "title": "A List-Processing Approach to Compute Voronoi Diagrams and the Euclidean Distance Transform", "doi": null, "abstractUrl": "/journal/tp/1998/07/i0757/13rRUy0HYKO", "parentPublication": { "id": "trans/tp", "title": "IEEE Transactions on Pattern Analysis & Machine Intelligence", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "mags/cs/2016/03/mcs2016030088", "title": "Parallel Voronoi Computation for Physics-Based Simulations", "doi": null, "abstractUrl": "/magazine/cs/2016/03/mcs2016030088/13rRUy3xYb8", 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{ "issue": { "id": "1zKXryr0JDG", "title": "Feb.", "year": "2022", "issueNum": "02", "idPrefix": "tg", "pubType": "journal", "volume": "28", "label": "Feb.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "1m3m8X0HNF6", "doi": "10.1109/TVCG.2020.3014474", "abstract": "This article presents a real-time bokeh rendering technique that splats pre-computed sprites but takes dynamic visibilities and intrinsic appearances into account at runtime. To attain alias-free looks without excessive sampling on a lens, the visibilities of strong highlights are densely sampled using rasterization, while regular objects are sparsely sampled using conventional defocus-blur rendering. The intrinsic appearance is dynamically transformed from a precomputed look-up table, which encodes radial aberrations against image distances in a compact 2D texture. Our solution can render complex bokeh effects without undersampling artifacts in real time, and greatly improve the photorealism of defocus-blur rendering.", "abstracts": [ { "abstractType": "Regular", "content": "This article presents a real-time bokeh rendering technique that splats pre-computed sprites but takes dynamic visibilities and intrinsic appearances into account at runtime. To attain alias-free looks without excessive sampling on a lens, the visibilities of strong highlights are densely sampled using rasterization, while regular objects are sparsely sampled using conventional defocus-blur rendering. The intrinsic appearance is dynamically transformed from a precomputed look-up table, which encodes radial aberrations against image distances in a compact 2D texture. Our solution can render complex bokeh effects without undersampling artifacts in real time, and greatly improve the photorealism of defocus-blur rendering.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "This article presents a real-time bokeh rendering technique that splats pre-computed sprites but takes dynamic visibilities and intrinsic appearances into account at runtime. To attain alias-free looks without excessive sampling on a lens, the visibilities of strong highlights are densely sampled using rasterization, while regular objects are sparsely sampled using conventional defocus-blur rendering. The intrinsic appearance is dynamically transformed from a precomputed look-up table, which encodes radial aberrations against image distances in a compact 2D texture. Our solution can render complex bokeh effects without undersampling artifacts in real time, and greatly improve the photorealism of defocus-blur rendering.", "title": "Real-Time Dynamic Bokeh Rendering With Efficient Look-Up Table Sampling", "normalizedTitle": "Real-Time Dynamic Bokeh Rendering With Efficient Look-Up Table Sampling", "fno": "09159921", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Aberrations", "Image Reconstruction", "Image Restoration", "Image Texture", "Rendering Computer Graphics", "Conventional Defocus Blur Rendering", "Intrinsic Appearance", "Precomputed Look Up Table", "Complex Bokeh Effects", "Time Dynamic Bokeh Rendering", "Efficient Look Up Table", "Real Time Bokeh Rendering Technique", "Pre Computed Sprites", "Dynamic Visibilities", "Alias Free Looks", "Excessive Sampling", "Strong Highlights", "Regular Objects", "Rendering Computer Graphics", "Real Time Systems", "Lenses", "Table Lookup", "Sprites Computer", "Optical Imaging", "Ray Tracing", "Real Time Rendering", "Bokeh", "Depth Of Field", "Defocus Blur", "GPU" ], "authors": [ { "givenName": "Yuna", "surname": "Jeong", "fullName": "Yuna Jeong", "affiliation": "Korea Institute of Science and Technology Information (KISTI), Daejon, South Korea", "__typename": "ArticleAuthorType" }, { "givenName": "Seung Youp", "surname": "Baek", "fullName": "Seung Youp Baek", "affiliation": "Sungkyunkwan University (SKKU), Suwon, Gyeonggi-do, South Korea", "__typename": "ArticleAuthorType" }, { "givenName": "Yechan", "surname": "Seok", "fullName": "Yechan Seok", "affiliation": "Sungkyunkwan University (SKKU), Suwon, Gyeonggi-do, South Korea", "__typename": "ArticleAuthorType" }, { "givenName": "Gi Beom", "surname": "Lee", "fullName": "Gi Beom Lee", "affiliation": "Sungkyunkwan University (SKKU), Suwon, Gyeonggi-do, South Korea", "__typename": "ArticleAuthorType" }, { "givenName": "Sungkil", "surname": "Lee", "fullName": "Sungkil Lee", "affiliation": "Sungkyunkwan University (SKKU), Suwon, Gyeonggi-do, South Korea", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "02", "pubDate": "2022-02-01 00:00:00", "pubType": "trans", "pages": "1373-1384", "year": "2022", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/iccp/2009/4534/0/05559009", "title": "Image destabilization: Programmable defocus using lens and sensor motion", "doi": null, "abstractUrl": "/proceedings-article/iccp/2009/05559009/12OmNvxsSTw", "parentPublication": { "id": "proceedings/iccp/2009/4534/0", "title": "IEEE International Conference on Computational Photography (ICCP)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vv/1998/9180/0/91800135", "title": "Opacity-Weighted Color Interpolation, for Volume Sampling", "doi": null, "abstractUrl": 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and Defocus Effects from Natural Images with Aperture Rendering Neural Radiance Fields", "doi": null, "abstractUrl": "/proceedings-article/cvpr/2022/694600s8366/1H1jJ8eYZCo", "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/iccvw/2019/5023/0/502300d417", "title": "Depth-Guided Dense Dynamic Filtering Network for Bokeh Effect Rendering", "doi": null, "abstractUrl": "/proceedings-article/iccvw/2019/502300d417/1i5mB3Uf3gI", "parentPublication": { "id": "proceedings/iccvw/2019/5023/0", "title": "2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/cvprw/2020/9360/0/09151049", "title": "Rendering Natural Camera Bokeh Effect with Deep Learning", "doi": null, "abstractUrl": 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{ "issue": { "id": "1zKXryr0JDG", "title": "Feb.", "year": "2022", "issueNum": "02", "idPrefix": "tg", "pubType": "journal", "volume": "28", "label": "Feb.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "1lClkDMVdZK", "doi": "10.1109/TVCG.2020.3010236", "abstract": "We propose a fast and robust solver to simulate continuum-based deformable models with constraints, in particular, rigid-body and joint constraints useful for soft articulated characters. Our method embeds the degrees of freedom of both articulated rigid bodies and deformable bodies in one unified constrained optimization problem, thus coupling the deformable and rigid bodies. Inspired by Projective Dynamics which is a fast numerical solver to simulate deformable objects, we also propose a novel local/global solver that takes full advantage of the pre-factorized system matrices to accelerate the solve of our constrained optimization problem. Therefore, our method can efficiently simulate character models, with rigid-body parts (bones) being correctly coupled with deformable parts (flesh). Our method is stable because backward Euler time integration is applied to both rigid and deformable degrees of freedom. Our unified optimization problem is rigorously derived from constrained Newtonian mechanics. When simulating only articulated rigid bodies as a special case, our method converges to the state-of-the-art rigid body simulators.", "abstracts": [ { "abstractType": "Regular", "content": "We propose a fast and robust solver to simulate continuum-based deformable models with constraints, in particular, rigid-body and joint constraints useful for soft articulated characters. Our method embeds the degrees of freedom of both articulated rigid bodies and deformable bodies in one unified constrained optimization problem, thus coupling the deformable and rigid bodies. Inspired by Projective Dynamics which is a fast numerical solver to simulate deformable objects, we also propose a novel local/global solver that takes full advantage of the pre-factorized system matrices to accelerate the solve of our constrained optimization problem. Therefore, our method can efficiently simulate character models, with rigid-body parts (bones) being correctly coupled with deformable parts (flesh). Our method is stable because backward Euler time integration is applied to both rigid and deformable degrees of freedom. Our unified optimization problem is rigorously derived from constrained Newtonian mechanics. When simulating only articulated rigid bodies as a special case, our method converges to the state-of-the-art rigid body simulators.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "We propose a fast and robust solver to simulate continuum-based deformable models with constraints, in particular, rigid-body and joint constraints useful for soft articulated characters. Our method embeds the degrees of freedom of both articulated rigid bodies and deformable bodies in one unified constrained optimization problem, thus coupling the deformable and rigid bodies. Inspired by Projective Dynamics which is a fast numerical solver to simulate deformable objects, we also propose a novel local/global solver that takes full advantage of the pre-factorized system matrices to accelerate the solve of our constrained optimization problem. Therefore, our method can efficiently simulate character models, with rigid-body parts (bones) being correctly coupled with deformable parts (flesh). Our method is stable because backward Euler time integration is applied to both rigid and deformable degrees of freedom. Our unified optimization problem is rigorously derived from constrained Newtonian mechanics. When simulating only articulated rigid bodies as a special case, our method converges to the state-of-the-art rigid body simulators.", "title": "Soft Articulated Characters in Projective Dynamics", "normalizedTitle": "Soft Articulated Characters in Projective Dynamics", "fno": "09144462", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Computer Animation", "Deformation", "Image Representation", "Integration", "Matrix Algebra", "Optimisation", "Solid Modelling", "Soft Articulated Characters", "Projective Dynamics", "Continuum Based Deformable Models", "Unified Constrained Optimization Problem", "Deformable Objects", "Character Models", "Rigid Body Parts", "Deformable Parts", "Rigid Body Simulators", "Constrained Newtonian Mechanics", "Backward Euler Time Integration", "Deformable Models", "Computational Modeling", "Joints", "Bones", "Solid Modeling", "Couplings", "Numerical Models", "Rigid Body", "Deformable Body", "Coupling", "Projective Dynamics" ], "authors": [ { "givenName": "Jing", "surname": "Li", "fullName": "Jing Li", "affiliation": "School of Computing, University of Utah, Salt Lake City, UT, USA", "__typename": "ArticleAuthorType" }, { "givenName": "Tiantian", "surname": "Liu", "fullName": "Tiantian Liu", "affiliation": "Advanced Innovation Center For Future Visual Entertainment, Beijing Film Academy, Beijing, China", "__typename": "ArticleAuthorType" }, { "givenName": "Ladislav", "surname": "Kavan", "fullName": "Ladislav Kavan", "affiliation": "Microsoft Research Asia, Beijing, China", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "02", "pubDate": "2022-02-01 00:00:00", "pubType": "trans", "pages": "1385-1396", "year": "2022", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/cgi/2004/2171/0/21710327", "title": "Mixing Deformable and Rigid-Body Mechanics Simulation", "doi": null, "abstractUrl": "/proceedings-article/cgi/2004/21710327/12OmNASILTV", "parentPublication": { "id": "proceedings/cgi/2004/2171/0", "title": "Proceedings. Computer Graphics International", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/cvpr/2009/3992/0/05206602", "title": "Factorization for non-rigid and articulated structure using metric projections", "doi": null, "abstractUrl": "/proceedings-article/cvpr/2009/05206602/12OmNBKmXnl", "parentPublication": { "id": "proceedings/cvpr/2009/3992/0", "title": "2009 IEEE Conference on Computer Vision and Pattern Recognition", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iccv/2001/1143/1/00937545", "title": "Articulated soft objects for video-based body modeling", "doi": null, "abstractUrl": "/proceedings-article/iccv/2001/00937545/12OmNBOllh4", "parentPublication": { "id": "proceedings/iccv/2001/1143/1", "title": "Computer Vision, IEEE International Conference on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/wacv/2015/6683/0/6683a094", "title": "Non-rigid Articulated Point Set Registration for Human Pose Estimation", "doi": null, "abstractUrl": "/proceedings-article/wacv/2015/6683a094/12OmNC2OSPb", "parentPublication": { "id": "proceedings/wacv/2015/6683/0", "title": "2015 IEEE Winter Conference on Applications of Computer Vision (WACV)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/3dv/2017/2610/0/261001a038", "title": "Dynamic High Resolution Deformable Articulated Tracking", "doi": null, "abstractUrl": "/proceedings-article/3dv/2017/261001a038/12OmNqFa5nJ", "parentPublication": { "id": "proceedings/3dv/2017/2610/0", "title": "2017 International Conference on 3D Vision (3DV)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/cvpr/2014/5118/0/5118c353", "title": "Real-Time Simultaneous Pose and Shape Estimation for Articulated Objects Using a Single Depth Camera", "doi": null, "abstractUrl": "/proceedings-article/cvpr/2014/5118c353/12OmNvjyxy7", "parentPublication": { "id": "proceedings/cvpr/2014/5118/0", "title": "2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2010/01/ttg2010010070", "title": "Fluid Simulation with Articulated Bodies", "doi": null, "abstractUrl": "/journal/tg/2010/01/ttg2010010070/13rRUxDqS8f", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tp/2013/12/ttp2013122878", "title": "Articulated Human Detection with Flexible Mixtures of Parts", "doi": null, "abstractUrl": "/journal/tp/2013/12/ttp2013122878/13rRUxOveb0", "parentPublication": { "id": "trans/tp", "title": "IEEE Transactions on Pattern Analysis & Machine Intelligence", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/cvpr/2022/6946/0/694600n3191", "title": "COAP: Compositional Articulated Occupancy of People", "doi": null, "abstractUrl": "/proceedings-article/cvpr/2022/694600n3191/1H1jh510fDy", "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/cvpr/2021/4509/0/450900k0456", "title": "LEAP: Learning Articulated Occupancy of People", "doi": null, "abstractUrl": "/proceedings-article/cvpr/2021/450900k0456/1yeI08QZPbO", "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": "09159921", "articleId": "1m3m8X0HNF6", "__typename": "AdjacentArticleType" }, "next": { "fno": "09152170", "articleId": "1lRhwZDVlpm", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [ { "id": "1zKXvjglnuE", "name": "ttg202202-09144462s1-supp1-3010236.mp4", "location": "https://www.computer.org/csdl/api/v1/extra/ttg202202-09144462s1-supp1-3010236.mp4", "extension": "mp4", "size": "151 MB", "__typename": "WebExtraType" } ], "articleVideos": [] }
{ "issue": { "id": "1zKXryr0JDG", "title": "Feb.", "year": "2022", "issueNum": "02", "idPrefix": "tg", "pubType": "journal", "volume": "28", "label": "Feb.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "1lRhwZDVlpm", "doi": "10.1109/TVCG.2020.3012778", "abstract": "Studying variation among time-evolved translations is a valuable research area for cultural heritage. Understanding how and why translations vary reveals cultural, ideological, and even political influences on literature as well as author relations. In this article, we introduce a novel integrated visual application to support distant and close reading of a collection of Othello translations. We present a new interactive application that provides an alignment overview of all the translations and their correspondences in parallel with smooth zooming and panning capability to integrate distant and close reading within the same view. We provide a range of filtering and selection options to customize the alignment overview as well as focus on specific subsets. Selection and filtering are responsive to expert user preferences and update the analytical text metrics interactively. Also, we introduce a customized view for close reading which preserves the history of selections and the alignment overview state and enables backtracing and re-examining them. Finally, we present a new Term-Level Comparisons view (TLC) to compare and convey relative term weighting in the context of an alignment. Our visual design is guided by, used and evaluated by a domain expert specialist in German translations of Shakespeare.", "abstracts": [ { "abstractType": "Regular", "content": "Studying variation among time-evolved translations is a valuable research area for cultural heritage. Understanding how and why translations vary reveals cultural, ideological, and even political influences on literature as well as author relations. In this article, we introduce a novel integrated visual application to support distant and close reading of a collection of Othello translations. We present a new interactive application that provides an alignment overview of all the translations and their correspondences in parallel with smooth zooming and panning capability to integrate distant and close reading within the same view. We provide a range of filtering and selection options to customize the alignment overview as well as focus on specific subsets. Selection and filtering are responsive to expert user preferences and update the analytical text metrics interactively. Also, we introduce a customized view for close reading which preserves the history of selections and the alignment overview state and enables backtracing and re-examining them. Finally, we present a new Term-Level Comparisons view (TLC) to compare and convey relative term weighting in the context of an alignment. Our visual design is guided by, used and evaluated by a domain expert specialist in German translations of Shakespeare.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Studying variation among time-evolved translations is a valuable research area for cultural heritage. Understanding how and why translations vary reveals cultural, ideological, and even political influences on literature as well as author relations. In this article, we introduce a novel integrated visual application to support distant and close reading of a collection of Othello translations. We present a new interactive application that provides an alignment overview of all the translations and their correspondences in parallel with smooth zooming and panning capability to integrate distant and close reading within the same view. We provide a range of filtering and selection options to customize the alignment overview as well as focus on specific subsets. Selection and filtering are responsive to expert user preferences and update the analytical text metrics interactively. Also, we introduce a customized view for close reading which preserves the history of selections and the alignment overview state and enables backtracing and re-examining them. Finally, we present a new Term-Level Comparisons view (TLC) to compare and convey relative term weighting in the context of an alignment. Our visual design is guided by, used and evaluated by a domain expert specialist in German translations of Shakespeare.", "title": "TransVis: Integrated Distant and Close Reading of Othello Translations", "normalizedTitle": "TransVis: Integrated Distant and Close Reading of Othello Translations", "fno": "09152170", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Data Visualisation", "History", "Language Translation", "Text Analysis", "Othello Translations", "Cultural Heritage", "Cultural Influences", "Political Influences", "Integrated Visual Application", "Smooth Zooming", "Panning Capability", "Relative Term Weighting", "German Translations", "Term Level Comparisons View", "Ideological Influences", "Shakespeare", "Text Metrics", "Visualization", "Data Visualization", "Task Analysis", "Art", "Cultural Differences", "Euclidean Distance", "Text Visualization", "Othello", "Parallel Translations" ], "authors": [ { "givenName": "Mohammad", "surname": "Alharbi", "fullName": "Mohammad Alharbi", "affiliation": "Department of Computer Science, Swansea University, Swansea, UK", "__typename": "ArticleAuthorType" }, { "givenName": "Robert S", "surname": "Laramee", "fullName": "Robert S Laramee", "affiliation": "School of Computer Science, University of Nottingham, Nottingham, UK", "__typename": "ArticleAuthorType" }, { "givenName": "Tom", "surname": "Cheesman", "fullName": "Tom Cheesman", "affiliation": "College of Arts and Humanities, Swansea University, Swansea, UK", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "02", "pubDate": "2022-02-01 00:00:00", "pubType": "trans", "pages": "1397-1414", "year": "2022", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/icalt/2014/4038/0/4038a446", "title": "Theoretical Framework of Schematic Interactions Visualization in ESL Reading Teaching", "doi": null, "abstractUrl": "/proceedings-article/icalt/2014/4038a446/12OmNAZfxH5", "parentPublication": { "id": "proceedings/icalt/2014/4038/0", "title": "2014 IEEE 14th International Conference on Advanced Learning Technologies (ICALT)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/isai/2016/1585/0/1585a168", "title": "On Reading Changes under the Fragmentized Reading Environment and Application of Visual Thinking in the Design of Mobile Multimedia Reading Interface", "doi": null, "abstractUrl": "/proceedings-article/isai/2016/1585a168/12OmNBTJIOG", "parentPublication": { "id": "proceedings/isai/2016/1585/0", "title": "2016 International Conference on Information System and Artificial Intelligence (ISAI)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/ismar-amh/2012/4663/0/06483992", "title": "Tailoring the Adaptive Augmented Reality (A2R) museum visit: Identifying Cultural Heritage professionals' motivations and needs", "doi": null, "abstractUrl": "/proceedings-article/ismar-amh/2012/06483992/12OmNvyjGfR", "parentPublication": { "id": "proceedings/ismar-amh/2012/4663/0", "title": "2012 IEEE International Symposium on Mixed and Augmented Reality - Arts, Media, and Humanities (ISMAR-AMH)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/big-data/2017/2715/0/08257958", "title": "Universal distant reading through metadata proxies with archivespark", "doi": null, "abstractUrl": "/proceedings-article/big-data/2017/08257958/17D45VTRouq", "parentPublication": { "id": "proceedings/big-data/2017/2715/0", "title": "2017 IEEE International Conference on Big Data (Big Data)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "mags/cg/2020/04/09117084", "title": "Close Reading for Visualization Evaluation", "doi": null, "abstractUrl": "/magazine/cg/2020/04/09117084/1kGgoDW7R2E", "parentPublication": { "id": "mags/cg", "title": "IEEE Computer Graphics and Applications", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vis4dh/2020/9153/0/915300a001", "title": "Supporting Expert Close Analysis of Historical Scientific Writings: A Case Study for Near-by Reading", "doi": null, "abstractUrl": "/proceedings-article/vis4dh/2020/915300a001/1pZ0XNSkREs", "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/beliv/2020/9642/0/964200a029", "title": "Using Close Reading as a Method for Evaluating Visualizations", "doi": null, "abstractUrl": "/proceedings-article/beliv/2020/964200a029/1q0FO3J5Ogg", "parentPublication": { "id": "proceedings/beliv/2020/9642/0", "title": "2020 IEEE Workshop on Evaluation and Beyond - Methodological Approaches to Visualization (BELIV)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iv/2020/9134/0/913400a098", "title": "AlignVis: Semi-automatic Alignment and Visualization of Parallel Translations", "doi": null, "abstractUrl": "/proceedings-article/iv/2020/913400a098/1rSRdswuamQ", "parentPublication": { "id": "proceedings/iv/2020/9134/0", "title": "2020 24th International Conference Information Visualisation (IV)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icmcce/2020/2314/0/231400c381", "title": "A Study on the Reader Reception of English Translations of The Analects-Data Analysis with Python", "doi": null, "abstractUrl": "/proceedings-article/icmcce/2020/231400c381/1tzz7EN5NW8", "parentPublication": { "id": "proceedings/icmcce/2020/2314/0", "title": "2020 5th International Conference on Mechanical, Control and Computer Engineering (ICMCCE)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vis/2021/3335/0/333500a186", "title": "Text Visualization and Close Reading for Journalism with Storifier", "doi": null, "abstractUrl": "/proceedings-article/vis/2021/333500a186/1yXu8QMz7iw", "parentPublication": { "id": "proceedings/vis/2021/3335/0", "title": "2021 IEEE Visualization Conference (VIS)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "09144462", "articleId": "1lClkDMVdZK", "__typename": "AdjacentArticleType" }, "next": { "fno": "09146716", "articleId": "1lHjPSqVrpK", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [], "articleVideos": [] }
{ "issue": { "id": "1zKXryr0JDG", "title": "Feb.", "year": "2022", "issueNum": "02", "idPrefix": "tg", "pubType": "journal", "volume": "28", "label": "Feb.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "1lHjPSqVrpK", "doi": "10.1109/TVCG.2020.3011468", "abstract": "A commercial head-mounted display (HMD) for virtual reality (VR) presents three-dimensional imagery with a fixed focal distance. The VR HMD with a fixed focus can cause visual discomfort to an observer. In this article, we propose a novel design of a compact VR HMD supporting near-correct focus cues over a wide depth of field (from 18 cm to optical infinity). The proposed HMD consists of a low-resolution binary backlight, a liquid crystal display panel, and focus-tunable lenses. In the proposed system, the backlight locally illuminates the display panel that is floated by the focus-tunable lens at a specific distance. The illumination moment and the focus-tunable lens&#x2019; focal power are synchronized to generate focal blocks at the desired distances. The distance of each focal block is determined by depth information of three-dimensional imagery to provide near-correct focus cues. We evaluate the focus cue fidelity of the proposed system considering the fill factor and resolution of the backlight. Finally, we verify the display performance with experimental results.", "abstracts": [ { "abstractType": "Regular", "content": "A commercial head-mounted display (HMD) for virtual reality (VR) presents three-dimensional imagery with a fixed focal distance. The VR HMD with a fixed focus can cause visual discomfort to an observer. In this article, we propose a novel design of a compact VR HMD supporting near-correct focus cues over a wide depth of field (from 18 cm to optical infinity). The proposed HMD consists of a low-resolution binary backlight, a liquid crystal display panel, and focus-tunable lenses. In the proposed system, the backlight locally illuminates the display panel that is floated by the focus-tunable lens at a specific distance. The illumination moment and the focus-tunable lens&#x2019; focal power are synchronized to generate focal blocks at the desired distances. The distance of each focal block is determined by depth information of three-dimensional imagery to provide near-correct focus cues. We evaluate the focus cue fidelity of the proposed system considering the fill factor and resolution of the backlight. Finally, we verify the display performance with experimental results.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "A commercial head-mounted display (HMD) for virtual reality (VR) presents three-dimensional imagery with a fixed focal distance. The VR HMD with a fixed focus can cause visual discomfort to an observer. In this article, we propose a novel design of a compact VR HMD supporting near-correct focus cues over a wide depth of field (from 18 cm to optical infinity). The proposed HMD consists of a low-resolution binary backlight, a liquid crystal display panel, and focus-tunable lenses. In the proposed system, the backlight locally illuminates the display panel that is floated by the focus-tunable lens at a specific distance. The illumination moment and the focus-tunable lens’ focal power are synchronized to generate focal blocks at the desired distances. The distance of each focal block is determined by depth information of three-dimensional imagery to provide near-correct focus cues. We evaluate the focus cue fidelity of the proposed system considering the fill factor and resolution of the backlight. Finally, we verify the display performance with experimental results.", "title": "Volumetric Head-Mounted Display With Locally Adaptive Focal Blocks", "normalizedTitle": "Volumetric Head-Mounted Display With Locally Adaptive Focal Blocks", "fno": "09146716", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Helmet Mounted Displays", "Holographic Optical Elements", "Lenses", "Liquid Crystal Displays", "Optical Focusing", "Virtual Reality", "Volumetric Head Mounted Display", "Locally Adaptive Focal Blocks", "Commercial Head Mounted Display", "Virtual Reality", "Three Dimensional Imagery", "Fixed Focal Distance", "Fixed Focus", "Visual Discomfort", "Compact VR HMD", "Near Correct Focus Cues", "Wide Depth", "Optical Infinity", "Low Resolution Binary Backlight", "Liquid Crystal Display Panel", "Focus Tunable Lens", "Specific Distance", "Illumination Moment", "Focal Block", "Desired Distances", "Depth Information", "Focus Cue Fidelity", "Display Performance", "Size 18 0 Cm", "Resists", "Light Emitting Diodes", "Visualization", "Image Reconstruction", "Liquid Crystal Displays", "Retina", "Optical Imaging", "Virtual Reality", "Head Mounted Display", "Three Dimensional Display", "Multifocal Display" ], "authors": [ { "givenName": "Dongheon", "surname": "Yoo", "fullName": "Dongheon Yoo", "affiliation": "School of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea", "__typename": "ArticleAuthorType" }, { "givenName": "Seungjae", "surname": "Lee", "fullName": "Seungjae Lee", "affiliation": "School of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea", "__typename": "ArticleAuthorType" }, { "givenName": "Youngjin", "surname": "Jo", "fullName": "Youngjin Jo", "affiliation": "School of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea", "__typename": "ArticleAuthorType" }, { "givenName": "Jaebum", "surname": "Cho", "fullName": "Jaebum Cho", "affiliation": "School of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea", "__typename": "ArticleAuthorType" }, { "givenName": "Suyeon", "surname": "Choi", "fullName": "Suyeon Choi", "affiliation": "Stanford University, Stanford, CA, USA", "__typename": "ArticleAuthorType" }, { "givenName": "Byoungho", "surname": "Lee", "fullName": "Byoungho Lee", "affiliation": "School of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "02", "pubDate": "2022-02-01 00:00:00", "pubType": "trans", "pages": "1415-1427", "year": "2022", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/vr/2016/0836/0/07504749", "title": "SharpView: Improved clarity of defocussed content on optical see-through head-mounted displays", "doi": null, "abstractUrl": "/proceedings-article/vr/2016/07504749/12OmNBBhN9g", "parentPublication": { "id": "proceedings/vr/2016/0836/0", "title": "2016 IEEE Virtual Reality (VR)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iccce/2016/2427/0/2427a126", "title": "Halal Kit Identifier Using Radio Frequency Identification Technology", "doi": null, "abstractUrl": "/proceedings-article/iccce/2016/2427a126/12OmNrJAdPc", "parentPublication": { "id": "proceedings/iccce/2016/2427/0", "title": "2016 International Conference on Computer and Communication Engineering (ICCCE)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/ismar/2008/2840/0/04637321", "title": "An optical see-through head mounted display with addressable focal planes", "doi": null, "abstractUrl": "/proceedings-article/ismar/2008/04637321/12OmNwe2IAw", "parentPublication": { "id": "proceedings/ismar/2008/2840/0", "title": "2008 7th IEEE/ACM International Symposium on Mixed and Augmented Reality", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/cbms/2016/9036/0/9036a355", "title": "Applicability of LED-Based Light Sources for Diabetic Retinopathy Detection in Retinal Imaging", "doi": null, "abstractUrl": "/proceedings-article/cbms/2016/9036a355/12OmNxu6pbL", "parentPublication": { "id": "proceedings/cbms/2016/9036/0", "title": "2016 IEEE 29th International Symposium on Computer-Based Medical Systems (CBMS)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/si/2006/10/01715347", "title": "HVS-aware dynamic backlight scaling in TFT-LCDs", "doi": null, "abstractUrl": "/journal/si/2006/10/01715347/13rRUxC0StC", "parentPublication": { "id": "trans/si", "title": "IEEE Transactions on Very Large Scale Integration (VLSI) Systems", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2010/03/ttg2010030381", "title": "A Novel Prototype for an Optical See-Through Head-Mounted Display with Addressable Focus Cues", "doi": null, "abstractUrl": "/journal/tg/2010/03/ttg2010030381/13rRUyYSWsN", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iisa/2018/8161/0/08633628", "title": "A Novel and Robust GreenSoul-ed Lighting Controller", "doi": null, "abstractUrl": "/proceedings-article/iisa/2018/08633628/17D45WrVgdE", "parentPublication": { "id": "proceedings/iisa/2018/8161/0", "title": "2018 9th International Conference on Information, Intelligence, Systems and Applications (IISA)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iciev-&-icivpr/2018/5163/0/08641067", "title": "IoT Enabled Smart Bicycle Safety System", "doi": null, "abstractUrl": "/proceedings-article/iciev-&-icivpr/2018/08641067/17PYEmtOUYp", "parentPublication": { "id": "proceedings/iciev-&-icivpr/2018/5163/0", "title": "2018 Joint 7th International Conference on Informatics, Electronics & Vision (ICIEV) and 2018 2nd International Conference on Imaging, Vision & Pattern Recognition (icIVPR)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2019/05/08676155", "title": "Varifocal Occlusion for Optical See-Through Head-Mounted Displays using a Slide Occlusion Mask", "doi": null, "abstractUrl": "/journal/tg/2019/05/08676155/18LFfGhc49i", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2020/05/08999805", "title": "Illuminated Focus: Vision Augmentation using Spatial Defocusing via Focal Sweep Eyeglasses and High-Speed Projector", "doi": null, "abstractUrl": "/journal/tg/2020/05/08999805/1hpPCtKIAaA", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "09152170", "articleId": "1lRhwZDVlpm", "__typename": "AdjacentArticleType" }, "next": { "fno": "09143472", "articleId": "1lxmwwX05lC", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [], "articleVideos": [] }
{ "issue": { "id": "1zKXryr0JDG", "title": "Feb.", "year": "2022", "issueNum": "02", "idPrefix": "tg", "pubType": "journal", "volume": "28", "label": "Feb.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "1lxmwwX05lC", "doi": "10.1109/TVCG.2020.3010088", "abstract": "The majority of virtual reality (VR) applications rely on audiovisual stimuli and do not exploit the addition of other sensory cues that could increase the potential of VR. This systematic review surveys the existing literature on multisensory VR and the impact of haptic, olfactory, and taste cues over audiovisual VR. The goal is to identify the extent to which multisensory stimuli affect the VR experience, which stimuli are used in multisensory VR, the type of VR setups used, and the application fields covered. An analysis of the 105 studies that met the eligibility criteria revealed that 84.8 percent of the studies show a positive impact of multisensory VR experiences. Haptics is the most commonly used stimulus in multisensory VR systems (86.6 percent). Non-immersive and immersive VR setups are preferred over semi-immersive setups. Regarding the application fields, a considerable part was adopted by health professionals and science and engineering professionals. We further conclude that smell and taste are still underexplored, and they can bring significant value to VR applications. More research is recommended on how to synthesize and deliver these stimuli, which still require complex and costly apparatus be integrated into the VR experience in a controlled and straightforward manner.", "abstracts": [ { "abstractType": "Regular", "content": "The majority of virtual reality (VR) applications rely on audiovisual stimuli and do not exploit the addition of other sensory cues that could increase the potential of VR. This systematic review surveys the existing literature on multisensory VR and the impact of haptic, olfactory, and taste cues over audiovisual VR. The goal is to identify the extent to which multisensory stimuli affect the VR experience, which stimuli are used in multisensory VR, the type of VR setups used, and the application fields covered. An analysis of the 105 studies that met the eligibility criteria revealed that 84.8 percent of the studies show a positive impact of multisensory VR experiences. Haptics is the most commonly used stimulus in multisensory VR systems (86.6 percent). Non-immersive and immersive VR setups are preferred over semi-immersive setups. Regarding the application fields, a considerable part was adopted by health professionals and science and engineering professionals. We further conclude that smell and taste are still underexplored, and they can bring significant value to VR applications. More research is recommended on how to synthesize and deliver these stimuli, which still require complex and costly apparatus be integrated into the VR experience in a controlled and straightforward manner.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "The majority of virtual reality (VR) applications rely on audiovisual stimuli and do not exploit the addition of other sensory cues that could increase the potential of VR. This systematic review surveys the existing literature on multisensory VR and the impact of haptic, olfactory, and taste cues over audiovisual VR. The goal is to identify the extent to which multisensory stimuli affect the VR experience, which stimuli are used in multisensory VR, the type of VR setups used, and the application fields covered. An analysis of the 105 studies that met the eligibility criteria revealed that 84.8 percent of the studies show a positive impact of multisensory VR experiences. Haptics is the most commonly used stimulus in multisensory VR systems (86.6 percent). Non-immersive and immersive VR setups are preferred over semi-immersive setups. Regarding the application fields, a considerable part was adopted by health professionals and science and engineering professionals. We further conclude that smell and taste are still underexplored, and they can bring significant value to VR applications. More research is recommended on how to synthesize and deliver these stimuli, which still require complex and costly apparatus be integrated into the VR experience in a controlled and straightforward manner.", "title": "Do Multisensory Stimuli Benefit the Virtual Reality Experience? A Systematic Review", "normalizedTitle": "Do Multisensory Stimuli Benefit the Virtual Reality Experience? A Systematic Review", "fno": "09143472", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Sensor Fusion", "Virtual Reality", "Audiovisual VR", "Multisensory VR Experiences", "Multisensory VR Systems", "Nonimmersive VR Setups", "Multisensory Stimuli Benefit", "Virtual Reality Experience", "Audiovisual Stimuli", "Sensory Cues", "Haptic Cues", "Olfactory Cues", "Taste Cues", "Systematics", "Haptic Interfaces", "Olfactory", "Statistical Analysis", "Virtual Environments", "Pain", "Systematic Review", "Virtual Reality", "Multisensory" ], "authors": [ { "givenName": "Miguel", "surname": "Melo", "fullName": "Miguel Melo", "affiliation": "INESC TEC, Porto, Portugal", "__typename": "ArticleAuthorType" }, { "givenName": "Guilherme", "surname": "Gonçalves", "fullName": "Guilherme Gonçalves", "affiliation": "INESC TEC, 4200–465 Porto, Portugal and Universidade de Trás-os-Montes e Alto Douro, Vila Real, Portugal", "__typename": "ArticleAuthorType" }, { "givenName": "Pedro", "surname": "Monteiro", "fullName": "Pedro Monteiro", "affiliation": "INESC TEC, 4200–465 Porto, Portugal and Universidade de Trás-os-Montes e Alto Douro, Vila Real, Portugal", "__typename": "ArticleAuthorType" }, { "givenName": "Hugo", "surname": "Coelho", "fullName": "Hugo Coelho", "affiliation": "INESC TEC, 4200–465 Porto, Portugal and Universidade de Trás-os-Montes e Alto Douro, Vila Real, Portugal", "__typename": "ArticleAuthorType" }, { "givenName": "José", "surname": "Vasconcelos-Raposo", "fullName": "José Vasconcelos-Raposo", "affiliation": "INESC TEC, 4200–465 Porto, Portugal and Universidade de Trás-os-Montes e Alto Douro, Vila Real, Portugal", "__typename": "ArticleAuthorType" }, { "givenName": "Maximino", "surname": "Bessa", "fullName": "Maximino Bessa", "affiliation": "INESC TEC, 4200–465 Porto, Portugal and Universidade de Trás-os-Montes e Alto Douro, Vila Real, Portugal", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "02", "pubDate": "2022-02-01 00:00:00", "pubType": "trans", "pages": "1428-1442", "year": "2022", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/vr/2018/3365/0/08446553", "title": "Multisensory Virtual Reality Exposure Therapy", "doi": null, "abstractUrl": "/proceedings-article/vr/2018/08446553/13bd1eOELLT", "parentPublication": { "id": "proceedings/vr/2018/3365/0", "title": "2018 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "mags/cg/2017/06/mcg2017060019", "title": "Experiencing the Sights, Smells, Sounds, and Climate of Southern Italy in VR", "doi": null, "abstractUrl": "/magazine/cg/2017/06/mcg2017060019/13rRUxDqSb2", "parentPublication": { "id": "mags/cg", "title": "IEEE Computer Graphics and Applications", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2022/05/09714043", "title": "Studying the Effects of Congruence of Auditory and Visual Stimuli on Virtual Reality Experiences", "doi": null, "abstractUrl": "/journal/tg/2022/05/09714043/1B0Y2dBeUi4", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icmew/2022/7218/0/09859362", "title": "Exploring Multisensory Feedback for Virtual Reality Relaxation", "doi": null, "abstractUrl": "/proceedings-article/icmew/2022/09859362/1G4F5nOkBNK", "parentPublication": { "id": "proceedings/icmew/2022/7218/0", "title": "2022 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2023/05/10049717", "title": "Eating, Smelling, and Seeing: Investigating Multisensory Integration and (In)congruent Stimuli while Eating in VR", "doi": null, "abstractUrl": "/journal/tg/2023/05/10049717/1KYostbG9gY", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/5555/01/10057483", "title": "Studying the Influence of Multisensory Stimuli on a Firefighting Training Virtual Environment", "doi": null, "abstractUrl": "/journal/tg/5555/01/10057483/1LbFmZlZK24", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2020/11/08756096", "title": "Impact of Different Sensory Stimuli on Presence in Credible Virtual Environments", "doi": null, "abstractUrl": "/journal/tg/2020/11/08756096/1bpYGVRBVYc", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vr/2019/1377/0/08797906", "title": "Haptic Force Guided Sound Synthesis in Multisensory Virtual Reality (VR) Simulation for Rigid-Fluid Interaction", "doi": null, "abstractUrl": "/proceedings-article/vr/2019/08797906/1cJ0NFasbcc", "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/vrw/2020/6532/0/09090609", "title": "Exploring Effect Of Different External Stimuli On Body Association In VR", "doi": null, "abstractUrl": "/proceedings-article/vrw/2020/09090609/1jIxuOtbTAQ", "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/vrw/2021/4057/0/405700a377", "title": "Multisensory Teleportation in Virtual Reality Applications", "doi": null, "abstractUrl": "/proceedings-article/vrw/2021/405700a377/1tnXGQKSUPm", "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": "09146716", "articleId": "1lHjPSqVrpK", "__typename": "AdjacentArticleType" }, "next": { "fno": "09161249", "articleId": "1m4yGPNpj9u", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [ { "id": "1zKXwoV7vI4", "name": "ttg202202-09143472s1-supp2-3010088.csv", "location": "https://www.computer.org/csdl/api/v1/extra/ttg202202-09143472s1-supp2-3010088.csv", "extension": "csv", "size": "50.9 kB", "__typename": "WebExtraType" }, { "id": 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{ "issue": { "id": "1zKXryr0JDG", "title": "Feb.", "year": "2022", "issueNum": "02", "idPrefix": "tg", "pubType": "journal", "volume": "28", "label": "Feb.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "1m4yGPNpj9u", "doi": "10.1109/TVCG.2020.3014614", "abstract": "Industrial Augmented Reality (iAR) has demonstrated its advantages to communicate technical information in the fields of maintenance, assembly, and training. However, literature is scattered among different visual assets (i.e., AR visual user interface elements associated with a real scene). In this work, we present a systematic literature review of visual assets used in these industrial fields. We searched five databases, initially finding 1757 papers. Then, we selected 122 iAR papers from 1997 to 2019 and extracted 348 visual assets. We propose a classification for visual assets according to (i) what is displayed, (ii) how it conveys information (frame of reference, color coding, animation), and, (iii) why it is used. Our review shows that product models, text and auxiliary models are, in order, the most common, with each most often used to support operating, checking and locating tasks respectively. Other visual assets are scarcely used. Product and auxiliary models are commonly rendered world-fixed, color coding is not used as often as expected, while animations are limited to product and auxiliary model. This survey provides a snapshot of over 20 years of literature in iAR, useful to understand established practices to orientate in iAR interface design and to present future research directions.", "abstracts": [ { "abstractType": "Regular", "content": "Industrial Augmented Reality (iAR) has demonstrated its advantages to communicate technical information in the fields of maintenance, assembly, and training. However, literature is scattered among different visual assets (i.e., AR visual user interface elements associated with a real scene). In this work, we present a systematic literature review of visual assets used in these industrial fields. We searched five databases, initially finding 1757 papers. Then, we selected 122 iAR papers from 1997 to 2019 and extracted 348 visual assets. We propose a classification for visual assets according to (i) what is displayed, (ii) how it conveys information (frame of reference, color coding, animation), and, (iii) why it is used. Our review shows that product models, text and auxiliary models are, in order, the most common, with each most often used to support operating, checking and locating tasks respectively. Other visual assets are scarcely used. Product and auxiliary models are commonly rendered world-fixed, color coding is not used as often as expected, while animations are limited to product and auxiliary model. This survey provides a snapshot of over 20 years of literature in iAR, useful to understand established practices to orientate in iAR interface design and to present future research directions.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Industrial Augmented Reality (iAR) has demonstrated its advantages to communicate technical information in the fields of maintenance, assembly, and training. However, literature is scattered among different visual assets (i.e., AR visual user interface elements associated with a real scene). In this work, we present a systematic literature review of visual assets used in these industrial fields. We searched five databases, initially finding 1757 papers. Then, we selected 122 iAR papers from 1997 to 2019 and extracted 348 visual assets. We propose a classification for visual assets according to (i) what is displayed, (ii) how it conveys information (frame of reference, color coding, animation), and, (iii) why it is used. Our review shows that product models, text and auxiliary models are, in order, the most common, with each most often used to support operating, checking and locating tasks respectively. Other visual assets are scarcely used. Product and auxiliary models are commonly rendered world-fixed, color coding is not used as often as expected, while animations are limited to product and auxiliary model. This survey provides a snapshot of over 20 years of literature in iAR, useful to understand established practices to orientate in iAR interface design and to present future research directions.", "title": "What, How, and Why are Visual Assets Used in Industrial Augmented Reality? A Systematic Review and Classification in Maintenance, Assembly, and Training (From 1997 to 2019)", "normalizedTitle": "What, How, and Why are Visual Assets Used in Industrial Augmented Reality? A Systematic Review and Classification in Maintenance, Assembly, and Training (From 1997 to 2019)", "fno": "09161249", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Assembling", "Augmented Reality", "Data Visualisation", "Maintenance Engineering", "Production Engineering Computing", "User Interfaces", "Industrial Augmented Reality", "AR Visual User Interface Elements", "Systematic Literature Review", "Visual Assets", "Color Coding", "Animations", "I AR Interface Design", "Visualization", "Augmented Reality", "Training", "Maintenance Engineering", "Hardware", "Systematics", "Manufacturing", "Augmented Reality", "Industry", "Reviews", "User Interfaces", "Visualization" ], "authors": [ { "givenName": "Michele", "surname": "Gattullo", "fullName": "Michele Gattullo", "affiliation": "Department of Mechanics, Mathematics, and Management, Polytechnic Institute of Bari, Bari, IT, Italy", "__typename": "ArticleAuthorType" }, { "givenName": "Alessandro", "surname": "Evangelista", "fullName": "Alessandro Evangelista", "affiliation": "Department of Mechanics, Mathematics, and Management, Polytechnic Institute of Bari, Bari, IT, Italy", "__typename": "ArticleAuthorType" }, { "givenName": "Antonio E.", "surname": "Uva", "fullName": "Antonio E. Uva", "affiliation": "Department of Mechanics, Mathematics, and Management, Polytechnic Institute of Bari, Bari, IT, Italy", "__typename": "ArticleAuthorType" }, { "givenName": "Michele", "surname": "Fiorentino", "fullName": "Michele Fiorentino", "affiliation": "Department of Mechanics, Mathematics, and Management, Polytechnic Institute of Bari, Bari, IT, Italy", "__typename": "ArticleAuthorType" }, { "givenName": "Joseph L.", "surname": "Gabbard", "fullName": "Joseph L. Gabbard", "affiliation": "Grado Department of Industrial & Systems Engineering, Virginia Tech, Blacksburg, VA, USA", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "02", "pubDate": "2022-02-01 00:00:00", "pubType": "trans", "pages": "1443-1456", "year": "2022", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/icebe/2013/5111/0/5111a162", "title": "Leveraging Assets as a Service for Business Intelligence in Manufacturing Service Ecosystems", "doi": null, "abstractUrl": "/proceedings-article/icebe/2013/5111a162/12OmNApu5Hv", "parentPublication": { "id": "proceedings/icebe/2013/5111/0", "title": "2013 IEEE 10th International Conference on e-Business Engineering (ICEBE)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iccms/2010/3941/1/3941a133", "title": "Key Technique of Assembly System in an Augmented Reality Environment", "doi": null, "abstractUrl": "/proceedings-article/iccms/2010/3941a133/12OmNqC2uYI", "parentPublication": { "id": "proceedings/iccms/2010/3941/1", "title": "Computer Modeling and Simulation, International Conference on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/wacv/2009/5497/0/05403093", "title": "Recovering the full pose from a single keyframe", "doi": null, "abstractUrl": "/proceedings-article/wacv/2009/05403093/12OmNqNXEpy", "parentPublication": { "id": "proceedings/wacv/2009/5497/0", "title": "2009 Workshop on Applications of Computer Vision (WACV 2009)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/ts/2012/06/tts2012061376", "title": "Modeling Product Line Software Assets Using Domain-Specific Kits", "doi": null, "abstractUrl": "/journal/ts/2012/06/tts2012061376/13rRUyYjKc3", "parentPublication": { "id": "trans/ts", "title": "IEEE Transactions on Software Engineering", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/compsac/2022/8810/0/881000a545", "title": "A Systematic Literature Review of Virtual and Augmented Reality Applications for Maintenance in Manufacturing", "doi": null, "abstractUrl": "/proceedings-article/compsac/2022/881000a545/1FJ5OxsS4Ba", "parentPublication": { "id": "proceedings/compsac/2022/8810/0", "title": "2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/ismar-adjunct/2022/5365/0/536500a060", "title": "Ready for Industrial Use? A User Study of Spatial Augmented Reality in Industrial Assembly", "doi": null, "abstractUrl": "/proceedings-article/ismar-adjunct/2022/536500a060/1J7WhVnnWpO", "parentPublication": { "id": "proceedings/ismar-adjunct/2022/5365/0", "title": "2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vrw/2020/6532/0/09090576", "title": "Augmented Reality for the Manufacturing Industry: The Case of an Assembly Assistant", "doi": null, "abstractUrl": "/proceedings-article/vrw/2020/09090576/1jIxw4eZW8M", "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/svr/2020/9231/0/923100a179", "title": "Augmented Reality for Manual Assembly in Industry 4.0: Gathering Guidelines", "doi": null, "abstractUrl": "/proceedings-article/svr/2020/923100a179/1oZBDyQMM6c", "parentPublication": { "id": "proceedings/svr/2020/9231/0", "title": "2020 22nd Symposium on Virtual and Augmented Reality (SVR)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/ismar-adjunct/2020/7675/0/767500a172", "title": "Design preferences on Industrial Augmented Reality: a survey with potential technical writers", "doi": null, "abstractUrl": "/proceedings-article/ismar-adjunct/2020/767500a172/1pBMjARVuEg", "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/2020/7675/0/767500a135", "title": "A User Study on AR-assisted Industrial Assembly", "doi": null, "abstractUrl": "/proceedings-article/ismar-adjunct/2020/767500a135/1pBMl1Z7xw4", "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" } ], "adjacentArticles": { "previous": { "fno": "09143472", "articleId": "1lxmwwX05lC", "__typename": "AdjacentArticleType" }, "next": null, "__typename": "AdjacentArticlesType" }, "webExtras": [], "articleVideos": [] }
{ "issue": { "id": "12OmNvAiSlz", "title": "January/February", "year": "2008", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "14", "label": "January/February", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUIJuxvf", "doi": "10.1109/TVCG.2007.70405", "abstract": "We propose an acceleration scheme for manybody dynamic collision detection at interactive rates. We use the VADOP, a tight bounding volume representation that offers fast update rates and which is particularly suitable for applications with many fast-moving objects. The axes selection that determines the shape of our bounding volumes is based on spherical coverings. We demonstrate that we can robustly detect collisions that are missed by pseudo-dynamic collision detection schemes, with even greater performance due to substantial collision pruning by our bounding volumes.", "abstracts": [ { "abstractType": "Regular", "content": "We propose an acceleration scheme for manybody dynamic collision detection at interactive rates. We use the VADOP, a tight bounding volume representation that offers fast update rates and which is particularly suitable for applications with many fast-moving objects. The axes selection that determines the shape of our bounding volumes is based on spherical coverings. We demonstrate that we can robustly detect collisions that are missed by pseudo-dynamic collision detection schemes, with even greater performance due to substantial collision pruning by our bounding volumes.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "We propose an acceleration scheme for manybody dynamic collision detection at interactive rates. We use the VADOP, a tight bounding volume representation that offers fast update rates and which is particularly suitable for applications with many fast-moving objects. The axes selection that determines the shape of our bounding volumes is based on spherical coverings. We demonstrate that we can robustly detect collisions that are missed by pseudo-dynamic collision detection schemes, with even greater performance due to substantial collision pruning by our bounding volumes.", "title": "Velocity-Aligned Discrete Oriented Polytopes for Dynamic Collision Detection", "normalizedTitle": "Velocity-Aligned Discrete Oriented Polytopes for Dynamic Collision Detection", "fno": "ttg2008010001", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Collision Detection", "Continuous Collision Detection", "Dynamic Collision Detection", "Physically Based Modeling", "Boundary Representations", "Virtual Reality" ], "authors": [ { "givenName": "Daniel S.", "surname": "Coming", "fullName": "Daniel S. Coming", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Oliver G.", "surname": "Staadt", "fullName": "Oliver G. Staadt", "affiliation": null, "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2008-01-01 00:00:00", "pubType": "trans", "pages": "1-12", "year": "2008", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/iccsee/2012/4647/3/4647c557", "title": "Collision Detection Research for Deformable Objects", "doi": null, "abstractUrl": "/proceedings-article/iccsee/2012/4647c557/12OmNAXxWYc", "parentPublication": { "id": "proceedings/iccsee/2012/4647/3", "title": "Computer Science and Electronics Engineering, International Conference on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iccsee/2012/4647/3/4647c547", "title": "The Algorithm of Fast Collision Detection Based on Hybrid Bounding Box", "doi": null, "abstractUrl": "/proceedings-article/iccsee/2012/4647c547/12OmNro0HX1", "parentPublication": { "id": "proceedings/iccsee/2012/4647/3", "title": "Computer Science and Electronics Engineering, International Conference on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/cis/2010/4297/0/4297a109", "title": "An Algorithm of Collision Detection Based on Hybrid Model", "doi": null, "abstractUrl": "/proceedings-article/cis/2010/4297a109/12OmNwbLVqf", "parentPublication": { "id": "proceedings/cis/2010/4297/0", "title": "2010 International Conference on Computational Intelligence and Security", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/pg/2001/1227/0/12270124", "title": "Dual Brep-CSG Collision Detection for General Polyhedra", "doi": null, "abstractUrl": "/proceedings-article/pg/2001/12270124/12OmNwtn3uG", "parentPublication": { "id": "proceedings/pg/2001/1227/0", "title": "Computer Graphics and Applications, Pacific Conference on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/ca/1999/0167/0/01670082", "title": "Real-time Collision Detection for Virtual Surgery", "doi": null, "abstractUrl": "/proceedings-article/ca/1999/01670082/12OmNzV70Or", "parentPublication": { "id": "proceedings/ca/1999/0167/0", "title": "Computer Animation", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/ifcsta/2009/3930/3/3930c410", "title": "A Collision Detection Method Based on the Virtual Occluders", "doi": null, "abstractUrl": "/proceedings-article/ifcsta/2009/3930c410/12OmNzVGcNi", "parentPublication": { "id": null, "title": null, "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iccsee/2012/4647/3/4647c538", "title": "The Collision Detection Algorithm in Virtual Reality", "doi": null, "abstractUrl": "/proceedings-article/iccsee/2012/4647c538/12OmNzWx0b7", "parentPublication": { "id": "proceedings/iccsee/2012/4647/3", "title": "Computer Science and Electronics Engineering, International Conference on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2004/06/v0649", "title": "Image-Based Collision Detection for Deformable Cloth Models", "doi": null, "abstractUrl": "/journal/tg/2004/06/v0649/13rRUNvgz9z", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2003/02/v0254", "title": "Image-Based Techniques in a Hybrid Collision Detector", "doi": null, "abstractUrl": "/journal/tg/2003/02/v0254/13rRUwh80H0", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "mags/cg/2006/01/mcg2006010064", "title": "Hierarchical Spherical Distance Fields for Collision Detection", "doi": null, "abstractUrl": "/magazine/cg/2006/01/mcg2006010064/13rRUxBJhoR", "parentPublication": { "id": "mags/cg", "title": "IEEE Computer Graphics and Applications", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": null, "next": { "fno": "ttg2008010013", "articleId": "13rRUxly95v", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [], "articleVideos": [] }
{ "issue": { "id": "12OmNvAiSlz", "title": "January/February", "year": "2008", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "14", "label": "January/February", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUxly95v", "doi": "10.1109/TVCG.2007.70413", "abstract": "Abstract—Photon mapping places an enormous burden on the memory hierarchy. Rendering a 512?512 image of a simple scene can require more than 196GB of raw bandwidth to the photon map data structure. This bandwidth is a major obstacle to real time photon mapping. This paper investigates two approaches for reducing the required bandwidth: 1) reordering the kNN searches; and 2) cache conscious data structures. Using a Hilbert curve reordering, we demonstrate an experimental lower bound of 15MB of bandwidth for the same scene. Unfortunately, this improvement of four orders of magnitude requires a prohibitive amount of intermediate storage. We introduce two novel cost-effective algorithms that reduce the bandwidth by one order of magnitude. Scenes of different complexities are shown to exhibit similar reductions in bandwidth. We explain why the choice of data structure does not achieve similar reductions. We also examine the interaction of query reordering with two photon map acceleration techniques, importance sampling and the irradiance cache. Query reordering exploits the additional coherence that arises from the use of importance sampling in scenes with glossy surfaces. Irradiance caching also benefits from query reordering, even when complex surface geometry reduces the effectiveness of the irradiance cache.", "abstracts": [ { "abstractType": "Regular", "content": "Abstract—Photon mapping places an enormous burden on the memory hierarchy. Rendering a 512?512 image of a simple scene can require more than 196GB of raw bandwidth to the photon map data structure. This bandwidth is a major obstacle to real time photon mapping. This paper investigates two approaches for reducing the required bandwidth: 1) reordering the kNN searches; and 2) cache conscious data structures. Using a Hilbert curve reordering, we demonstrate an experimental lower bound of 15MB of bandwidth for the same scene. Unfortunately, this improvement of four orders of magnitude requires a prohibitive amount of intermediate storage. We introduce two novel cost-effective algorithms that reduce the bandwidth by one order of magnitude. Scenes of different complexities are shown to exhibit similar reductions in bandwidth. We explain why the choice of data structure does not achieve similar reductions. We also examine the interaction of query reordering with two photon map acceleration techniques, importance sampling and the irradiance cache. Query reordering exploits the additional coherence that arises from the use of importance sampling in scenes with glossy surfaces. Irradiance caching also benefits from query reordering, even when complex surface geometry reduces the effectiveness of the irradiance cache.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Abstract—Photon mapping places an enormous burden on the memory hierarchy. Rendering a 512?512 image of a simple scene can require more than 196GB of raw bandwidth to the photon map data structure. This bandwidth is a major obstacle to real time photon mapping. This paper investigates two approaches for reducing the required bandwidth: 1) reordering the kNN searches; and 2) cache conscious data structures. Using a Hilbert curve reordering, we demonstrate an experimental lower bound of 15MB of bandwidth for the same scene. Unfortunately, this improvement of four orders of magnitude requires a prohibitive amount of intermediate storage. We introduce two novel cost-effective algorithms that reduce the bandwidth by one order of magnitude. Scenes of different complexities are shown to exhibit similar reductions in bandwidth. We explain why the choice of data structure does not achieve similar reductions. We also examine the interaction of query reordering with two photon map acceleration techniques, importance sampling and the irradiance cache. Query reordering exploits the additional coherence that arises from the use of importance sampling in scenes with glossy surfaces. Irradiance caching also benefits from query reordering, even when complex surface geometry reduces the effectiveness of the irradiance cache.", "title": "Reducing Photon-Mapping Bandwidth by Query Reordering", "normalizedTitle": "Reducing Photon-Mapping Bandwidth by Query Reordering", "fno": "ttg2008010013", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Bandwidth", "Layout", "Data Structures", "Lighting", "Casting", "Monte Carlo Methods", "Geometry", "Hardware", "Rendering Computer Graphics", "Acceleration", "Graphics Hardware", "Global Illumination", "Photon Mapping", "Importance Sampling", "Irradiance Caching" ], "authors": [ { "givenName": "Joshua", "surname": "Steinhurst", "fullName": "Joshua Steinhurst", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Greg", "surname": "Coombe", "fullName": "Greg Coombe", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Anselmo", "surname": "Lastra", "fullName": "Anselmo Lastra", "affiliation": "IEEE", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2008-01-01 00:00:00", "pubType": "trans", "pages": "13-24", "year": "2008", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/isms/2010/3973/0/3973a086", "title": "Artificial Neural Network Model for Spectral Construction of a Linear Accelerator Megavoltage Photon Beam", "doi": null, "abstractUrl": "/proceedings-article/isms/2010/3973a086/12OmNAR1aYy", "parentPublication": { "id": "proceedings/isms/2010/3973/0", "title": "Intelligent Systems, Modelling and Simulation, International Conference on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iiki/2016/5952/0/5952a022", "title": "Distributed Global Illumination Method Based on Photon Mapping", "doi": null, "abstractUrl": "/proceedings-article/iiki/2016/5952a022/12OmNBubOQf", "parentPublication": { "id": "proceedings/iiki/2016/5952/0", "title": "2016 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/rt/2007/1629/0/04342595", "title": "SIMD Packet Techniques for Photon Mapping", "doi": null, "abstractUrl": "/proceedings-article/rt/2007/04342595/12OmNrJAe8g", "parentPublication": { "id": "proceedings/rt/2007/1629/0", "title": "IEEE/ EG Symposium on Interactive Ray Tracing 2007", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/rt/2008/2741/0/04634633", "title": "Adaptive ray packet reordering", "doi": null, "abstractUrl": "/proceedings-article/rt/2008/04634633/12OmNzvhvB6", "parentPublication": { "id": "proceedings/rt/2008/2741/0", "title": "Symposium on Interactive Ray Tracing", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/sc/2014/5500/0/5500a921", "title": "Parallelization of Reordering Algorithms for Bandwidth and Wavefront Reduction", "doi": null, "abstractUrl": "/proceedings-article/sc/2014/5500a921/12OmNzwpU8u", "parentPublication": { "id": "proceedings/sc/2014/5500/0", "title": "SC14: International Conference for High Performance Computing, Networking, Storage and Analysis", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/si/2015/12/07006785", "title": "A 2-GHz bandwidth, integrated transimpedance amplifier for single-photon timing applications", "doi": null, "abstractUrl": "/journal/si/2015/12/07006785/13rRUIM2VES", "parentPublication": { "id": "trans/si", "title": "IEEE Transactions on Very Large Scale Integration (VLSI) Systems", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2017/01/07534852", "title": "Correlated Photon Mapping for Interactive Global Illumination of Time-Varying Volumetric Data", "doi": null, "abstractUrl": "/journal/tg/2017/01/07534852/13rRUxZ0o1E", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2012/12/ttg2012122364", "title": "Historygrams: Enabling Interactive Global Illumination in Direct Volume Rendering using Photon Mapping", "doi": null, "abstractUrl": "/journal/tg/2012/12/ttg2012122364/13rRUyYjK5h", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2013/08/ttg2013081317", "title": "Real-Time Volume Rendering in Dynamic Lighting Environments Using Precomputed Photon Mapping", "doi": null, "abstractUrl": "/journal/tg/2013/08/ttg2013081317/13rRUynHuja", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2021/11/09523836", "title": "Foveated Photon Mapping", "doi": null, "abstractUrl": "/journal/tg/2021/11/09523836/1wpquR1qr1S", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "ttg2008010001", "articleId": "13rRUIJuxvf", "__typename": "AdjacentArticleType" }, "next": { "fno": "ttg2008010025", "articleId": "13rRUxBrGgP", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [], "articleVideos": [] }
{ "issue": { "id": "12OmNvAiSlz", "title": "January/February", "year": "2008", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "14", "label": "January/February", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUxBrGgP", "doi": "10.1109/TVCG.2007.1067", "abstract": "Stretch-free surface flattening has been requested by a variety of applications. At present, the most difficult problem is how to segment a given model into nearly developable atlases so that a nearly stretch-free flattening can be computed. The criterion for segmentation is needed to evaluate the possibility of flattening a given surface patch, which should be fast computed. In this paper, we present a method to compute the length-preserved free boundary (LPFB) of a mesh patch which speeds up the mesh parameterization. The distortion on parameterization can then be employed as the criterion in a trial-and-error algorithm for segmenting a given model into nearly developable atlases. The computation of LPFB is formulated as a numerical optimization problem in the angle space, where we are trying to optimize the angle excesses on the boundary while preserving the constraints derived from the closed-path theorem and the length preservation.", "abstracts": [ { "abstractType": "Regular", "content": "Stretch-free surface flattening has been requested by a variety of applications. At present, the most difficult problem is how to segment a given model into nearly developable atlases so that a nearly stretch-free flattening can be computed. The criterion for segmentation is needed to evaluate the possibility of flattening a given surface patch, which should be fast computed. In this paper, we present a method to compute the length-preserved free boundary (LPFB) of a mesh patch which speeds up the mesh parameterization. The distortion on parameterization can then be employed as the criterion in a trial-and-error algorithm for segmenting a given model into nearly developable atlases. The computation of LPFB is formulated as a numerical optimization problem in the angle space, where we are trying to optimize the angle excesses on the boundary while preserving the constraints derived from the closed-path theorem and the length preservation.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Stretch-free surface flattening has been requested by a variety of applications. At present, the most difficult problem is how to segment a given model into nearly developable atlases so that a nearly stretch-free flattening can be computed. The criterion for segmentation is needed to evaluate the possibility of flattening a given surface patch, which should be fast computed. In this paper, we present a method to compute the length-preserved free boundary (LPFB) of a mesh patch which speeds up the mesh parameterization. The distortion on parameterization can then be employed as the criterion in a trial-and-error algorithm for segmenting a given model into nearly developable atlases. The computation of LPFB is formulated as a numerical optimization problem in the angle space, where we are trying to optimize the angle excesses on the boundary while preserving the constraints derived from the closed-path theorem and the length preservation.", "title": "Computing Length-Preserved Free Boundary for Quasi-Developable Mesh Segmentation", "normalizedTitle": "Computing Length-Preserved Free Boundary for Quasi-Developable Mesh Segmentation", "fno": "ttg2008010025", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Boundary Representations", "Geometric Algorithms", "Languages", "And Systems" ], "authors": [ { "givenName": "Charlie", "surname": "Wang", "fullName": "Charlie Wang", "affiliation": null, "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2008-01-01 00:00:00", "pubType": "trans", "pages": "25-36", "year": "2008", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/ieee-vis/2001/7200/0/7200ying", "title": "Nonmanifold Subdivision", "doi": null, "abstractUrl": "/proceedings-article/ieee-vis/2001/7200ying/12OmNBuL14k", "parentPublication": { "id": "proceedings/ieee-vis/2001/7200/0", "title": "Visualization Conference, IEEE", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/ipps/1994/5602/0/0288311", "title": "Transformations between boundary codes, run length codes, and linear quadtrees", "doi": null, "abstractUrl": "/proceedings-article/ipps/1994/0288311/12OmNwHyZZp", "parentPublication": { "id": "proceedings/ipps/1994/5602/0", "title": "Parallel Processing Symposium, International", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2009/03/ttg2009030504", "title": "Computing Teichmüller Shape Space", "doi": null, "abstractUrl": "/journal/tg/2009/03/ttg2009030504/13rRUx0gezR", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2013/01/ttg2013010016", "title": "Efficient Boundary Extraction of BSP Solids Based on Clipping Operations", "doi": null, "abstractUrl": "/journal/tg/2013/01/ttg2013010016/13rRUx0xPIF", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tp/2012/08/06112767", "title": "Handwritten Chinese Text Recognition by Integrating Multiple Contexts", "doi": null, "abstractUrl": "/journal/tp/2012/08/06112767/13rRUxBa5t4", "parentPublication": { "id": "trans/tp", "title": "IEEE Transactions on Pattern Analysis & Machine Intelligence", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2005/02/v0181", "title": "Sharpen&Bend: Recovering Curved Sharp Edges in Triangle Meshes Produced by Feature-Insensitive Sampling", "doi": null, "abstractUrl": "/journal/tg/2005/02/v0181/13rRUxDIth6", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2008/05/ttg2008051030", "title": "Discrete Surface Ricci Flow", "doi": null, "abstractUrl": "/journal/tg/2008/05/ttg2008051030/13rRUyfbwqB", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2008/04/ttg2008040805", "title": "Globally Optimal Surface Mapping for Surfaces with Arbitrary Topology", "doi": null, "abstractUrl": "/journal/tg/2008/04/ttg2008040805/13rRUygT7su", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2006/04/v0629", "title": "Bilateral Recovering of Sharp Edges on Feature-Insensitive Sampled Meshes", "doi": null, "abstractUrl": "/journal/tg/2006/04/v0629/13rRUynHuiY", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "ttg2008010013", "articleId": "13rRUxly95v", "__typename": "AdjacentArticleType" }, "next": { "fno": "ttg2008010047", "articleId": "13rRUygT7y4", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [], "articleVideos": [] }
{ "issue": { "id": "12OmNvAiSlz", "title": "January/February", "year": "2008", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "14", "label": "January/February", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUygT7y4", "doi": "10.1109/TVCG.2007.70415", "abstract": "Providing appropriate methods to facilitate the analysis of time-oriented data is a key issue in many application domains. In this paper, we focus on the unique role of the parameter time in the context of visually driven data analysis.We will discuss three major aspects — visualization, analysis, and the user. It will be illustrated that it is necessary to consider the characteristics of time when generating visual representations.For that purpose we take a look at different types of time and present visual examples. Integrating visual and analytical methods has become an increasingly important issue. Therefore, we present our experiences in temporal data abstraction, principal component analysis, and clustering of larger volumes of time-oriented data. The third main aspect we discuss is supporting user-centered visual analysis.We describe event-based visualization as a promising means to adapt the visualization pipeline to needs and tasks of users.", "abstracts": [ { "abstractType": "Regular", "content": "Providing appropriate methods to facilitate the analysis of time-oriented data is a key issue in many application domains. In this paper, we focus on the unique role of the parameter time in the context of visually driven data analysis.We will discuss three major aspects — visualization, analysis, and the user. It will be illustrated that it is necessary to consider the characteristics of time when generating visual representations.For that purpose we take a look at different types of time and present visual examples. Integrating visual and analytical methods has become an increasingly important issue. Therefore, we present our experiences in temporal data abstraction, principal component analysis, and clustering of larger volumes of time-oriented data. The third main aspect we discuss is supporting user-centered visual analysis.We describe event-based visualization as a promising means to adapt the visualization pipeline to needs and tasks of users.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Providing appropriate methods to facilitate the analysis of time-oriented data is a key issue in many application domains. In this paper, we focus on the unique role of the parameter time in the context of visually driven data analysis.We will discuss three major aspects — visualization, analysis, and the user. It will be illustrated that it is necessary to consider the characteristics of time when generating visual representations.For that purpose we take a look at different types of time and present visual examples. Integrating visual and analytical methods has become an increasingly important issue. Therefore, we present our experiences in temporal data abstraction, principal component analysis, and clustering of larger volumes of time-oriented data. The third main aspect we discuss is supporting user-centered visual analysis.We describe event-based visualization as a promising means to adapt the visualization pipeline to needs and tasks of users.", "title": "Visual Methods for Analyzing Time-Oriented Data", "normalizedTitle": "Visual Methods for Analyzing Time-Oriented Data", "fno": "ttg2008010047", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Time Oriented Data", "Visualization", "Analysis", "User" ], "authors": [ { "givenName": "Wolfgang", "surname": "Aigner", "fullName": "Wolfgang Aigner", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Silvia", "surname": "Miksch", "fullName": "Silvia Miksch", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Wolfgang", "surname": "Müller", "fullName": "Wolfgang Müller", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Heidrun", "surname": "Schumann", "fullName": "Heidrun Schumann", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Christian", "surname": "Tominski", "fullName": "Christian Tominski", "affiliation": null, "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2008-01-01 00:00:00", "pubType": "trans", "pages": "47-60", "year": "2008", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/vast/2012/4752/0/06400553", "title": "Visual analytics methods for categoric spatio-temporal data", "doi": null, "abstractUrl": "/proceedings-article/vast/2012/06400553/12OmNB8TU3x", "parentPublication": { "id": "proceedings/vast/2012/4752/0", "title": "2012 IEEE Conference on Visual Analytics Science and Technology (VAST 2012)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vast/2014/6227/0/07042498", "title": "TimeGraph: A data management framework for visual analytics of large multivariate time-oriented networks", "doi": null, "abstractUrl": "/proceedings-article/vast/2014/07042498/12OmNBlXs3i", "parentPublication": { "id": "proceedings/vast/2014/6227/0", "title": "2014 IEEE Conference on Visual Analytics Science and Technology (VAST)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iwooos/1995/7115/0/71150103", "title": "An Open Visual Model for Object-Oriented Operating Systems", "doi": null, "abstractUrl": "/proceedings-article/iwooos/1995/71150103/12OmNqH9hej", "parentPublication": { "id": "proceedings/iwooos/1995/7115/0", "title": "Object-Orientation in Operating Systems, International Workshop on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iv/2012/4771/0/4771a030", "title": "Animation for Time-oriented Data: An Overview of Empirical Research", "doi": null, "abstractUrl": "/proceedings-article/iv/2012/4771a030/12OmNvvLi3Q", "parentPublication": { "id": "proceedings/iv/2012/4771/0", "title": "2012 16th International Conference on Information Visualisation", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iv/2009/3733/0/3733a044", "title": "Hierarchical Temporal Patterns and Interactive Aggregated Views for Pixel-Based Visualizations", "doi": null, "abstractUrl": "/proceedings-article/iv/2009/3733a044/12OmNxAlA96", "parentPublication": { "id": "proceedings/iv/2009/3733/0", "title": "2009 13th International Conference Information Visualisation", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/isorc/1999/0207/0/02070165", "title": "An Integrated Environment for the Complete Development Cycle of an Object-Oriented Distributed Real-Time System", "doi": null, "abstractUrl": "/proceedings-article/isorc/1999/02070165/12OmNyuPLfU", "parentPublication": { "id": "proceedings/isorc/1999/0207/0", "title": "Proceedings 2nd IEEE International Symposium on Object-Oriented Real-Time Distributed Computing (ISORC'99) (Cat. No.99-61702)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icdmw/2010/4257/0/4257a396", "title": "Analysing the Large-Scale, Time-Oriented, VAST 2010 MC2 Dataset with PRISMA", "doi": null, "abstractUrl": "/proceedings-article/icdmw/2010/4257a396/12OmNzFdtaR", "parentPublication": { "id": "proceedings/icdmw/2010/4257/0", "title": "2010 IEEE International Conference on Data Mining Workshops", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "mags/cg/2016/04/mcg2016040008", "title": "Topic- and Time-Oriented Visual Text Analysis", "doi": null, "abstractUrl": "/magazine/cg/2016/04/mcg2016040008/13rRUx0xPpt", "parentPublication": { "id": "mags/cg", "title": "IEEE Computer Graphics and Applications", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2014/12/06875957", "title": "Visual Methods for Analyzing Probabilistic Classification Data", "doi": null, "abstractUrl": "/journal/tg/2014/12/06875957/13rRUxBrGh0", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2013/12/ttg2013122247", "title": "TimeBench: A Data Model and Software Library for Visual Analytics of Time-Oriented Data", "doi": null, "abstractUrl": "/journal/tg/2013/12/ttg2013122247/13rRUxZ0o1A", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "ttg2008010025", "articleId": "13rRUxBrGgP", "__typename": "AdjacentArticleType" }, "next": { "fno": "ttg2008010037", "articleId": "13rRUxD9gXz", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [], "articleVideos": [] }
{ "issue": { "id": "12OmNvAiSlz", "title": "January/February", "year": "2008", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "14", "label": "January/February", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUxD9gXz", "doi": "10.1109/TVCG.2007.70437", "abstract": "We propose a novel approach to proportional derivative (PD) control exploiting the fact that these equations can be solved analytically for a single degree of freedom. The analytic solution indicates what the PD controller would accomplish in isolation without interference from neighboring joints, gravity and external forces, outboard limbs, etc. Our approach to time integration includes an inverse dynamics formulation that automatically incorporates global feedback so that the per joint predictions are achieved. This effectively decouples stiffness from control so that we obtain the desired target regardless of the stiffness of the joint, which merely determines when we get there. We start with simple examples to illustrate our method, and then move on to more complex examples including PD control of line segment muscle actuators.", "abstracts": [ { "abstractType": "Regular", "content": "We propose a novel approach to proportional derivative (PD) control exploiting the fact that these equations can be solved analytically for a single degree of freedom. The analytic solution indicates what the PD controller would accomplish in isolation without interference from neighboring joints, gravity and external forces, outboard limbs, etc. Our approach to time integration includes an inverse dynamics formulation that automatically incorporates global feedback so that the per joint predictions are achieved. This effectively decouples stiffness from control so that we obtain the desired target regardless of the stiffness of the joint, which merely determines when we get there. We start with simple examples to illustrate our method, and then move on to more complex examples including PD control of line segment muscle actuators.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "We propose a novel approach to proportional derivative (PD) control exploiting the fact that these equations can be solved analytically for a single degree of freedom. The analytic solution indicates what the PD controller would accomplish in isolation without interference from neighboring joints, gravity and external forces, outboard limbs, etc. Our approach to time integration includes an inverse dynamics formulation that automatically incorporates global feedback so that the per joint predictions are achieved. This effectively decouples stiffness from control so that we obtain the desired target regardless of the stiffness of the joint, which merely determines when we get there. We start with simple examples to illustrate our method, and then move on to more complex examples including PD control of line segment muscle actuators.", "title": "Impulse-Based Control of Joints and Muscles", "normalizedTitle": "Impulse-Based Control of Joints and Muscles", "fno": "ttg2008010037", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Computer Graphics", "Physically Based Modeling", "Animation", "Kinematics And Dynamics" ], "authors": [ { "givenName": "Rachel", "surname": "Weinstein", "fullName": "Rachel Weinstein", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Eran", "surname": "Guendelman", "fullName": "Eran Guendelman", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Ronald", "surname": "Fedkiw", "fullName": "Ronald Fedkiw", "affiliation": null, "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2008-01-01 00:00:00", "pubType": "trans", "pages": "37-46", "year": "2008", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/cisis/2009/3575/0/3575b217", "title": "Application of Cylindrical Elastic Elements for Stiffness Control of Tendon-Driven Manipulator and Inverse Kinematics Evaluation", "doi": null, "abstractUrl": "/proceedings-article/cisis/2009/3575b217/12OmNASraJx", "parentPublication": { "id": "proceedings/cisis/2009/3575/0", "title": "2009 International Conference on Complex, Intelligent and Software Intensive Systems", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/robot/1992/2720/0/00220285", "title": "Adaptive integral manifold control of flexible joint robot manipulators", "doi": null, "abstractUrl": "/proceedings-article/robot/1992/00220285/12OmNAkWvfb", "parentPublication": { "id": "proceedings/robot/1992/2720/0", "title": "Proceedings 1992 IEEE International Conference on Robotics and Automation", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/robot/1988/0852/0/00012252", "title": "Robust independent robot joint control: design and experimentation", "doi": null, "abstractUrl": "/proceedings-article/robot/1988/00012252/12OmNwkR5vx", "parentPublication": { "id": "proceedings/robot/1988/0852/0", "title": "Proceedings. 1988 IEEE International Conference on Robotics and Automation", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icmeae/2015/8328/0/07386219", "title": "Comparative Study of a PID and PD Control Bounded by Hyperbolic Tangent Function in Robot 3 DOF", "doi": null, "abstractUrl": "/proceedings-article/icmeae/2015/07386219/12OmNwvVrH3", "parentPublication": { "id": "proceedings/icmeae/2015/8328/0", "title": "2015 International Conference on Mechatronics, Electronics and Automotive Engineering (ICMEAE)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/robot/1989/1938/0/00099978", "title": "Dynamics coordination in a manipulator with 7 joints", "doi": null, "abstractUrl": "/proceedings-article/robot/1989/00099978/12OmNxeutbT", "parentPublication": { "id": "proceedings/robot/1989/1938/0", "title": "1989 IEEE International Conference on Robotics and Automation", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/robot/1988/0852/0/00012199", "title": "Dynamics based control of vertically articulated manipulators", "doi": null, "abstractUrl": "/proceedings-article/robot/1988/00012199/12OmNzVXNNv", "parentPublication": { "id": "proceedings/robot/1988/0852/0", "title": "Proceedings. 1988 IEEE International Conference on Robotics and Automation", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/robot/1989/1938/0/00100166", "title": "Open-loop stiffness control of overconstrained mechanisms/robotic linkage systems", "doi": null, "abstractUrl": "/proceedings-article/robot/1989/00100166/12OmNzYNN14", "parentPublication": { "id": "proceedings/robot/1989/1938/0", "title": "1989 IEEE International Conference on Robotics and Automation", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "mags/cg/2011/04/mcg2011040056", "title": "Direct Control of Simulated Nonhuman Characters", "doi": null, "abstractUrl": "/magazine/cg/2011/04/mcg2011040056/13rRUwInv93", "parentPublication": { "id": "mags/cg", "title": "IEEE Computer Graphics and Applications", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2008/01/ttg2008010173", "title": "Psychologically Inspired Anticipation and Dynamic Response for Impacts to the Head and Upper Body", "doi": null, "abstractUrl": "/journal/tg/2008/01/ttg2008010173/13rRUygT7f3", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2012/02/ttg2012020228", "title": "Cubical Mass-Spring Model Design Based on a Tensile Deformation Test and Nonlinear Material Model", "doi": null, "abstractUrl": "/journal/tg/2012/02/ttg2012020228/13rRUygT7y7", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "ttg2008010047", "articleId": "13rRUygT7y4", "__typename": "AdjacentArticleType" }, "next": { "fno": "ttg2008010061", "articleId": "13rRUxlgy3x", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [], "articleVideos": [] }
{ "issue": { "id": "12OmNvAiSlz", "title": "January/February", "year": "2008", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "14", "label": "January/February", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUxlgy3x", "doi": "10.1109/TVCG.2007.70426", "abstract": "Information uncertainty is inherent in many problems and is often subtle and complicated to understand. While visualization is a powerful means for exploring and understanding information, information uncertainty visualization is ad hoc and not widespread. This paper identifies two main barriers to the uptake of information uncertainty visualization: firstly, the difficulty of modeling and propagating the uncertainty information; and secondly, the difficulty of mapping uncertainty to visual elements. To overcome these barriers, we extend the spreadsheet paradigm to encapsulate uncertainty details within cells. This creates an inherent awareness of the uncertainty associated with each variable. The spreadsheet can hide the uncertainty details, enabling the user to think simply in terms of variables. Furthermore, the system can aid with automated propagation of uncertainty information, since it is intrinsically aware of the uncertainty. The system also enables mapping the encapsulated uncertainty to visual elements via the formula language and a visualization sheet. Support for such low-level visual mapping provides flexibility to explore new techniques for information uncertainty visualization.", "abstracts": [ { "abstractType": "Regular", "content": "Information uncertainty is inherent in many problems and is often subtle and complicated to understand. While visualization is a powerful means for exploring and understanding information, information uncertainty visualization is ad hoc and not widespread. This paper identifies two main barriers to the uptake of information uncertainty visualization: firstly, the difficulty of modeling and propagating the uncertainty information; and secondly, the difficulty of mapping uncertainty to visual elements. To overcome these barriers, we extend the spreadsheet paradigm to encapsulate uncertainty details within cells. This creates an inherent awareness of the uncertainty associated with each variable. The spreadsheet can hide the uncertainty details, enabling the user to think simply in terms of variables. Furthermore, the system can aid with automated propagation of uncertainty information, since it is intrinsically aware of the uncertainty. The system also enables mapping the encapsulated uncertainty to visual elements via the formula language and a visualization sheet. Support for such low-level visual mapping provides flexibility to explore new techniques for information uncertainty visualization.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Information uncertainty is inherent in many problems and is often subtle and complicated to understand. While visualization is a powerful means for exploring and understanding information, information uncertainty visualization is ad hoc and not widespread. This paper identifies two main barriers to the uptake of information uncertainty visualization: firstly, the difficulty of modeling and propagating the uncertainty information; and secondly, the difficulty of mapping uncertainty to visual elements. To overcome these barriers, we extend the spreadsheet paradigm to encapsulate uncertainty details within cells. This creates an inherent awareness of the uncertainty associated with each variable. The spreadsheet can hide the uncertainty details, enabling the user to think simply in terms of variables. Furthermore, the system can aid with automated propagation of uncertainty information, since it is intrinsically aware of the uncertainty. The system also enables mapping the encapsulated uncertainty to visual elements via the formula language and a visualization sheet. Support for such low-level visual mapping provides flexibility to explore new techniques for information uncertainty visualization.", "title": "A Spreadsheet Approach to Facilitate Visualization of Uncertainty in Information", "normalizedTitle": "A Spreadsheet Approach to Facilitate Visualization of Uncertainty in Information", "fno": "ttg2008010061", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Uncertainty Visualization", "Information Uncertainty", "Fuzzy Visualization", "Visualization Process", "Visualization Framework", "Information Modeling" ], "authors": [ { "givenName": "Alexander", "surname": "Streit", "fullName": "Alexander Streit", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Binh", "surname": "Pham", "fullName": "Binh Pham", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Ross", "surname": "Brown", "fullName": "Ross Brown", "affiliation": null, "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2008-01-01 00:00:00", "pubType": "trans", "pages": "61-72", "year": "2008", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/ieee-infovis/1997/8189/0/81890017", "title": "A spreadsheet approach to information visualization", "doi": null, "abstractUrl": "/proceedings-article/ieee-infovis/1997/81890017/12OmNApcuwH", "parentPublication": { "id": "proceedings/ieee-infovis/1997/8189/0", "title": "Information Visualization, IEEE Symposium on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/ieee-infovis/1996/7668/0/76680070", "title": "FINESSE: a financial information spreadsheet", "doi": null, "abstractUrl": "/proceedings-article/ieee-infovis/1996/76680070/12OmNBiygyk", "parentPublication": { "id": "proceedings/ieee-infovis/1996/7668/0", "title": "Information Visualization, IEEE Symposium on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vlhcc/2014/4035/0/06883040", "title": "Visualizing the problem domain for spreadsheet users: A mental model perspective", "doi": null, "abstractUrl": "/proceedings-article/vlhcc/2014/06883040/12OmNx1Iw8e", "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": "mags/cg/2013/01/mcg2013010075", "title": "Visualization of Uncertainty without a Mean", "doi": null, "abstractUrl": "/magazine/cg/2013/01/mcg2013010075/13rRUwcAquB", "parentPublication": { "id": "mags/cg", "title": "IEEE Computer Graphics and Applications", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2009/06/ttg2009061209", "title": "A User Study to Compare Four Uncertainty Visualization Methods for 1D and 2D Datasets", "doi": null, "abstractUrl": "/journal/tg/2009/06/ttg2009061209/13rRUxcsYLI", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2019/01/08457476", "title": "In Pursuit of Error: A Survey of Uncertainty Visualization Evaluation", "doi": null, "abstractUrl": "/journal/tg/2019/01/08457476/17D45WaTkcP", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2023/01/09904442", "title": "Communicating Uncertainty in Digital Humanities Visualization Research", "doi": null, "abstractUrl": "/journal/tg/2023/01/09904442/1H1gpt871W8", "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/2023/02/09566799", "title": "Fuzzy Spreadsheet: Understanding and Exploring Uncertainties in Tabular Calculations", "doi": null, "abstractUrl": "/journal/tg/2023/02/09566799/1xC6REtgYiA", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vis4dh/2021/1370/0/137000a012", "title": "Uncertainty-aware Topic Modeling Visualization", "doi": null, "abstractUrl": "/proceedings-article/vis4dh/2021/137000a012/1yNiG9yU9JS", "parentPublication": { "id": "proceedings/vis4dh/2021/1370/0", "title": "2021 IEEE 6th Workshop on Visualization for the Digital Humanities (VIS4DH)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "ttg2008010037", "articleId": "13rRUxD9gXz", "__typename": "AdjacentArticleType" }, "next": { "fno": "ttg2008010073", "articleId": "13rRUxAAT7x", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [], "articleVideos": [] }
{ "issue": { "id": "12OmNvAiSlz", "title": "January/February", "year": "2008", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "14", "label": "January/February", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUxAAT7x", "doi": "10.1109/TVCG.2007.70407", "abstract": "Abstract—This paper presents the layer-based representation of polyhedrons and its use for point-in-polyhedron tests. In the representation, the facets and edges of a polyhedron are sequentially arranged, and so the binary search algorithm is efficiently used to speed up inclusion tests. In comparison with conventional representation for polyhedrons, the layer-based representation we propose greatly reduces the storage requirement because it represents much information implicitly, though it still has a storage complexity O(n). It is simple to implement, and robust for inclusion tests because many singularities are erased in constructing the layer-based representation. Incorporating an octree structure for organizing polyhedrons, our approach can run at a speed comparable with BSP-based inclusion tests, and at the same time greatly reduce storage and preprocessing time in treating large polyhedrons. We have developed an efficient solution for point-in-polyhedron tests with the time complexity varying between O(n) and O(log n), depending on the polyhedron shape and the constructed representation, and less than O(log^3 n) in most cases. The time complexity of preprocess is between O(n) and O(n^2), varying with polyhedrons, where n is the edge number of a polyhedron.", "abstracts": [ { "abstractType": "Regular", "content": "Abstract—This paper presents the layer-based representation of polyhedrons and its use for point-in-polyhedron tests. In the representation, the facets and edges of a polyhedron are sequentially arranged, and so the binary search algorithm is efficiently used to speed up inclusion tests. In comparison with conventional representation for polyhedrons, the layer-based representation we propose greatly reduces the storage requirement because it represents much information implicitly, though it still has a storage complexity O(n). It is simple to implement, and robust for inclusion tests because many singularities are erased in constructing the layer-based representation. Incorporating an octree structure for organizing polyhedrons, our approach can run at a speed comparable with BSP-based inclusion tests, and at the same time greatly reduce storage and preprocessing time in treating large polyhedrons. We have developed an efficient solution for point-in-polyhedron tests with the time complexity varying between O(n) and O(log n), depending on the polyhedron shape and the constructed representation, and less than O(log^3 n) in most cases. The time complexity of preprocess is between O(n) and O(n^2), varying with polyhedrons, where n is the edge number of a polyhedron.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Abstract—This paper presents the layer-based representation of polyhedrons and its use for point-in-polyhedron tests. In the representation, the facets and edges of a polyhedron are sequentially arranged, and so the binary search algorithm is efficiently used to speed up inclusion tests. In comparison with conventional representation for polyhedrons, the layer-based representation we propose greatly reduces the storage requirement because it represents much information implicitly, though it still has a storage complexity O(n). It is simple to implement, and robust for inclusion tests because many singularities are erased in constructing the layer-based representation. Incorporating an octree structure for organizing polyhedrons, our approach can run at a speed comparable with BSP-based inclusion tests, and at the same time greatly reduce storage and preprocessing time in treating large polyhedrons. We have developed an efficient solution for point-in-polyhedron tests with the time complexity varying between O(n) and O(log n), depending on the polyhedron shape and the constructed representation, and less than O(log^3 n) in most cases. The time complexity of preprocess is between O(n) and O(n^2), varying with polyhedrons, where n is the edge number of a polyhedron.", "title": "Layer-Based Representation of Polyhedrons for Point Containment Tests", "normalizedTitle": "Layer-Based Representation of Polyhedrons for Point Containment Tests", "fno": "ttg2008010073", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Computational Geometry", "Polyhedron", "Point Containment", "Solid Representation" ], "authors": [ { "givenName": "Wencheng", "surname": "Wang", "fullName": "Wencheng Wang", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Jing", "surname": "Li", "fullName": "Jing Li", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Hanqiu", "surname": "Sun", "fullName": "Hanqiu Sun", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Enhua", "surname": "Wu", "fullName": "Enhua Wu", "affiliation": null, "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2008-01-01 00:00:00", "pubType": "trans", "pages": "73-83", "year": "2008", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/sibgrapi/2000/0878/0/08780235", "title": "Parallelization of Filling Algorithms on Distributed Memory Machines using the Point Containment Paradigm", "doi": null, "abstractUrl": "/proceedings-article/sibgrapi/2000/08780235/12OmNAfPIOL", "parentPublication": { "id": "proceedings/sibgrapi/2000/0878/0", "title": "Proceedings 13th Brazilian Symposium on Computer Graphics and Image Processing (Cat. No.PR00878)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/focs/1995/7183/0/71830092", "title": "A representation of cuts within 6/5 times the edge connectivity with applications", "doi": null, "abstractUrl": "/proceedings-article/focs/1995/71830092/12OmNC4wtyP", "parentPublication": { "id": "proceedings/focs/1995/7183/0", "title": "Proceedings of IEEE 36th Annual Foundations of Computer Science", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/focs/1995/7183/0/71830258", "title": "Improved lower bound on testing membership to a polyhedron by algebraic decision trees", "doi": null, "abstractUrl": "/proceedings-article/focs/1995/71830258/12OmNyen1kj", "parentPublication": { "id": "proceedings/focs/1995/7183/0", "title": "Proceedings of IEEE 36th Annual Foundations of Computer Science", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/spdp/1992/3200/0/0242705", "title": "Efficient networks for realizing point-to-point assignments in parallel processors", "doi": null, "abstractUrl": "/proceedings-article/spdp/1992/0242705/12OmNyfdOJ9", "parentPublication": { "id": "proceedings/spdp/1992/3200/0", "title": "Parallel and Distributed Processing, IEEE Symposium on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tc/1975/08/01672914", "title": "On the Floating Point Representation of Complex Numbers", "doi": null, "abstractUrl": "/journal/tc/1975/08/01672914/13rRUwhHcI0", "parentPublication": { "id": "trans/tc", "title": "IEEE Transactions on Computers", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tp/2007/01/i0159", "title": "The Number of N-Point Digital Discs", "doi": null, "abstractUrl": "/journal/tp/2007/01/i0159/13rRUxYrbNn", "parentPublication": { "id": "trans/tp", "title": "IEEE Transactions on Pattern Analysis & Machine Intelligence", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tc/1971/12/01671767", "title": "Tapered Floating Point: A New Floating-Point Representation", "doi": null, "abstractUrl": "/journal/tc/1971/12/01671767/13rRUyuvRvT", "parentPublication": { "id": "trans/tc", "title": "IEEE Transactions on Computers", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/wacv/2022/0915/0/091500a256", "title": "EllipsoidNet: Ellipsoid Representation for Point Cloud Classification and Segmentation", "doi": null, "abstractUrl": "/proceedings-article/wacv/2022/091500a256/1B13cXxY0b6", "parentPublication": { "id": "proceedings/wacv/2022/0915/0", "title": "2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iccv/2021/2812/0/281200g383", "title": "Geometry-Aware Self-Training for Unsupervised Domain Adaptation on Object Point Clouds", "doi": null, "abstractUrl": "/proceedings-article/iccv/2021/281200g383/1BmG4XlYzqo", "parentPublication": { "id": "proceedings/iccv/2021/2812/0", "title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/ictai/2021/0898/0/089800b480", "title": "Geometric Invariant Representation Learning for 3D Point Cloud", "doi": null, "abstractUrl": "/proceedings-article/ictai/2021/089800b480/1zw6hJOIDcs", "parentPublication": { "id": "proceedings/ictai/2021/0898/0", "title": "2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "ttg2008010061", "articleId": "13rRUxlgy3x", "__typename": "AdjacentArticleType" }, "next": { "fno": "ttg2008010084", "articleId": "13rRUwI5TXu", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [], "articleVideos": [] }
{ "issue": { "id": "12OmNvAiSlz", "title": "January/February", "year": "2008", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "14", "label": "January/February", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUwI5TXu", "doi": "10.1109/TVCG.2007.70410", "abstract": "Abstract—Ultimately, a display device should be capable of reproducing the visual effects observed in reality. In this paper we introduce an autostereoscopic display that uses a scalable array of digital light projectors and a projection screen augmented with microlenses to simulate a light field for a given three-dimensional scene. Physical objects emit or reflect light in all directions to create a light field that can be approximated by the light field display. The display can simultaneously provide many viewers from different viewpoints a stereoscopic effect without headtracking or special viewing glasses. This work focuses on two important technical problems related to the light field display; calibration and rendering. We present a solution to automatically calibrate the light field display using a camera and introduce two efficient algorithms to render the special multi-view images by exploiting their spatial coherence. The effectiveness of our approach is demonstrated with a four-projector prototype that can display dynamic imagery with full parallax.", "abstracts": [ { "abstractType": "Regular", "content": "Abstract—Ultimately, a display device should be capable of reproducing the visual effects observed in reality. In this paper we introduce an autostereoscopic display that uses a scalable array of digital light projectors and a projection screen augmented with microlenses to simulate a light field for a given three-dimensional scene. Physical objects emit or reflect light in all directions to create a light field that can be approximated by the light field display. The display can simultaneously provide many viewers from different viewpoints a stereoscopic effect without headtracking or special viewing glasses. This work focuses on two important technical problems related to the light field display; calibration and rendering. We present a solution to automatically calibrate the light field display using a camera and introduce two efficient algorithms to render the special multi-view images by exploiting their spatial coherence. The effectiveness of our approach is demonstrated with a four-projector prototype that can display dynamic imagery with full parallax.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Abstract—Ultimately, a display device should be capable of reproducing the visual effects observed in reality. In this paper we introduce an autostereoscopic display that uses a scalable array of digital light projectors and a projection screen augmented with microlenses to simulate a light field for a given three-dimensional scene. Physical objects emit or reflect light in all directions to create a light field that can be approximated by the light field display. The display can simultaneously provide many viewers from different viewpoints a stereoscopic effect without headtracking or special viewing glasses. This work focuses on two important technical problems related to the light field display; calibration and rendering. We present a solution to automatically calibrate the light field display using a camera and introduce two efficient algorithms to render the special multi-view images by exploiting their spatial coherence. The effectiveness of our approach is demonstrated with a four-projector prototype that can display dynamic imagery with full parallax.", "title": "Toward the Light Field Display: Autostereoscopic Rendering via a Cluster of Projectors", "normalizedTitle": "Toward the Light Field Display: Autostereoscopic Rendering via a Cluster of Projectors", "fno": "ttg2008010084", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Virtual Reality", "Display Algorithms", "Projector Calibration", "Image Based Rendering" ], "authors": [ { "givenName": "Ruigang", "surname": "Yang", "fullName": "Ruigang Yang", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Xinyu", "surname": "Huang", "fullName": "Xinyu Huang", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Sifang", "surname": "Li", "fullName": "Sifang Li", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Christopher", "surname": "Jaynes", "fullName": "Christopher Jaynes", "affiliation": null, "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2008-01-01 00:00:00", "pubType": "trans", "pages": "84-96", "year": "2008", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/cvmp/2010/4268/0/4268a123", "title": "Helium3D: A Laser-Based 3D Display with '3D+' Capability", "doi": null, "abstractUrl": "/proceedings-article/cvmp/2010/4268a123/12OmNAoDhXO", "parentPublication": { "id": "proceedings/cvmp/2010/4268/0", "title": "2010 Conference on Visual Media Production", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vr/2006/0224/0/02240281", "title": "A Foveal Inset for Large Display Environments", "doi": null, "abstractUrl": "/proceedings-article/vr/2006/02240281/12OmNrkT7BT", "parentPublication": { "id": "proceedings/vr/2006/0224/0", "title": "IEEE Virtual Reality Conference (VR 2006)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/apcip/2009/3699/2/3699b031", "title": "3D Multi-view Autostereoscopic Display and Its Key Technologie", "doi": null, "abstractUrl": "/proceedings-article/apcip/2009/3699b031/12OmNvAS4pe", "parentPublication": { "id": "proceedings/apcip/2009/3699/1", "title": "Information Processing, Asia-Pacific Conference on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vr/2006/0224/0/01667679", "title": "Long Visualization Depth Autostereoscopic Display using Light Field Rendering based Integral Videography", "doi": null, "abstractUrl": "/proceedings-article/vr/2006/01667679/12OmNvDZEZe", "parentPublication": { "id": "proceedings/vr/2006/0224/0", "title": "IEEE Virtual Reality Conference (VR 2006)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iv/2006/2602/0/26020778", "title": "A Projection-Based Multi-view Time-multiplexed Autostereoscopic 3D Display System", "doi": null, "abstractUrl": "/proceedings-article/iv/2006/26020778/12OmNwDSdGX", "parentPublication": { "id": "proceedings/iv/2006/2602/0", "title": "Tenth International Conference on Information Visualisation (IV'06)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/3dui/2007/0907/0/04142851", "title": "Character Interaction System with Autostereoscopic Display and Range Sensor", "doi": null, "abstractUrl": "/proceedings-article/3dui/2007/04142851/12OmNwc3wsr", "parentPublication": { "id": "proceedings/3dui/2007/0907/0", "title": "2007 IEEE Symposium on 3D User Interfaces", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vr/2004/8415/0/84150059", "title": "TWISTER: An Immersive Autostereoscopic Display", "doi": null, "abstractUrl": "/proceedings-article/vr/2004/84150059/12OmNx5piYo", "parentPublication": { "id": "proceedings/vr/2004/8415/0", "title": "Virtual Reality Conference, IEEE", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iccis/2012/4789/0/4789a009", "title": "A Synthetic Color Correction Method of Multi-projectors Display System", "doi": null, "abstractUrl": "/proceedings-article/iccis/2012/4789a009/12OmNzd7bXc", "parentPublication": { "id": "proceedings/iccis/2012/4789/0", "title": "2012 Fourth International Conference on Computational and Information Sciences", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "mags/co/2005/08/r8031", "title": "Autostereoscopic 3D Displays", "doi": null, "abstractUrl": "/magazine/co/2005/08/r8031/13rRUB7a16j", "parentPublication": { "id": "mags/co", "title": "Computer", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2007/03/v0508", "title": "Shadow Elimination and Blinding Light Suppression for Interactive Projected Displays", "doi": null, "abstractUrl": "/journal/tg/2007/03/v0508/13rRUxDIth7", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "ttg2008010073", "articleId": "13rRUxAAT7x", "__typename": "AdjacentArticleType" }, "next": { "fno": "ttg2008010097", "articleId": "13rRUwhpBE2", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [], "articleVideos": [] }
{ "issue": { "id": "12OmNvAiSlz", "title": "January/February", "year": "2008", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "14", "label": "January/February", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUwhpBE2", "doi": "10.1109/TVCG.2007.1052", "abstract": "Recent radiometric compensation techniques make it possible to project images onto colored and textured surfaces. This is realized with projector-camera systems by scanning the projection surface on a per-pixel basis. Using the captured information, a compensation image is calculated that neutralizes geometric distortions and color blending caused by the underlying surface. As a result, the brightness and the contrast of the input image is reduced compared to a conventional projection onto a white canvas. If the input image is not manipulated in its intensities, the compensation image can contain values that are outside the dynamic range of the projector. These will lead to clipping errors and to visible artifacts on the surface. In this article, we present an innovative algorithm that dynamically adjusts the content of the input images before radiometric compensation is carried out. This reduces the perceived visual artifacts while simultaneously preserving a maximum of luminance and contrast. The algorithm is implemented entirely on the GPU and is the first of its kind to run in real-time.", "abstracts": [ { "abstractType": "Regular", "content": "Recent radiometric compensation techniques make it possible to project images onto colored and textured surfaces. This is realized with projector-camera systems by scanning the projection surface on a per-pixel basis. Using the captured information, a compensation image is calculated that neutralizes geometric distortions and color blending caused by the underlying surface. As a result, the brightness and the contrast of the input image is reduced compared to a conventional projection onto a white canvas. If the input image is not manipulated in its intensities, the compensation image can contain values that are outside the dynamic range of the projector. These will lead to clipping errors and to visible artifacts on the surface. In this article, we present an innovative algorithm that dynamically adjusts the content of the input images before radiometric compensation is carried out. This reduces the perceived visual artifacts while simultaneously preserving a maximum of luminance and contrast. The algorithm is implemented entirely on the GPU and is the first of its kind to run in real-time.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Recent radiometric compensation techniques make it possible to project images onto colored and textured surfaces. This is realized with projector-camera systems by scanning the projection surface on a per-pixel basis. Using the captured information, a compensation image is calculated that neutralizes geometric distortions and color blending caused by the underlying surface. As a result, the brightness and the contrast of the input image is reduced compared to a conventional projection onto a white canvas. If the input image is not manipulated in its intensities, the compensation image can contain values that are outside the dynamic range of the projector. These will lead to clipping errors and to visible artifacts on the surface. In this article, we present an innovative algorithm that dynamically adjusts the content of the input images before radiometric compensation is carried out. This reduces the perceived visual artifacts while simultaneously preserving a maximum of luminance and contrast. The algorithm is implemented entirely on the GPU and is the first of its kind to run in real-time.", "title": "Real-Time Adaptive Radiometric Compensation", "normalizedTitle": "Real-Time Adaptive Radiometric Compensation", "fno": "ttg2008010097", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Computer Graphics", "Picture Image Generation", "Display Algorithms", "Image Processing", "Computer Vision", "Radiometry", "Reflectance", "Enhancement", "Color" ], "authors": [ { "givenName": "Anselm", "surname": "Grundh?fer", "fullName": "Anselm Grundh?fer", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Oliver", "surname": "Bimber", "fullName": "Oliver Bimber", "affiliation": null, "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2008-01-01 00:00:00", "pubType": "trans", "pages": "97-108", "year": "2008", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/ismar/2008/2840/0/04637343", "title": "A practical radiometric compensation method for projector-based augmentation", "doi": null, "abstractUrl": "/proceedings-article/ismar/2008/04637343/12OmNBp52JR", "parentPublication": { "id": "proceedings/ismar/2008/2840/0", "title": "2008 7th IEEE/ACM International Symposium on Mixed and Augmented Reality", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/pg/2007/3009/0/30090391", "title": "Radiometric Compensation through Inverse Light Transport", "doi": null, "abstractUrl": "/proceedings-article/pg/2007/30090391/12OmNqIzgUn", "parentPublication": { "id": "proceedings/pg/2007/3009/0", "title": "Computer Graphics and Applications, Pacific Conference on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/cvpr/2017/0457/0/0457d596", "title": "Simultaneous Geometric and Radiometric Calibration of a Projector-Camera Pair", "doi": null, "abstractUrl": "/proceedings-article/cvpr/2017/0457d596/12OmNwpGgNQ", "parentPublication": { "id": "proceedings/cvpr/2017/0457/0", "title": "2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iccv/2009/4420/0/05459418", "title": "Radiometric compensation using stratified inverses", "doi": null, "abstractUrl": "/proceedings-article/iccv/2009/05459418/12OmNxFJXtd", "parentPublication": { "id": "proceedings/iccv/2009/4420/0", "title": "2009 IEEE 12th International Conference on Computer Vision (ICCV)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iccvw/2011/0063/0/06130328", "title": "Photometric stereo with auto-radiometric calibration", "doi": null, "abstractUrl": "/proceedings-article/iccvw/2011/06130328/12OmNyPQ4A9", "parentPublication": { "id": "proceedings/iccvw/2011/0063/0", "title": "2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/cvprw/2005/2660/0/237230100", "title": "Radiometric Compensation in a Projector-Camera System Based Properties of Human Vision System", "doi": null, "abstractUrl": "/proceedings-article/cvprw/2005/237230100/12OmNzVoBRi", "parentPublication": { "id": "proceedings/cvprw/2005/2660/0", "title": "2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2015/11/07164338", "title": "Radiometric Compensation for Cooperative Distributed Multi-Projection System Through 2-DOF Distributed Control", "doi": null, "abstractUrl": "/journal/tg/2015/11/07164338/13rRUIIVlkk", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2016/11/07523376", "title": "Real-Time Radiometric Compensation for Optical See-Through Head-Mounted Displays", "doi": null, "abstractUrl": "/journal/tg/2016/11/07523376/13rRUxASu0P", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vrw/2022/8402/0/840200a750", "title": "Perceptually-Based Optimization for Radiometric Projector Compensation", "doi": null, "abstractUrl": "/proceedings-article/vrw/2022/840200a750/1CJd3VypH7G", "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/cvprw/2019/2506/0/250600b899", "title": "FRESCO: Fast Radiometric Egocentric Screen Compensation", "doi": null, "abstractUrl": "/proceedings-article/cvprw/2019/250600b899/1iTvvExuDBe", "parentPublication": { "id": "proceedings/cvprw/2019/2506/0", "title": "2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "ttg2008010084", "articleId": "13rRUwI5TXu", "__typename": "AdjacentArticleType" }, "next": { "fno": "ttg2008010109", "articleId": "13rRUzpzeAW", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [], "articleVideos": [] }
{ "issue": { "id": "12OmNvAiSlz", "title": "January/February", "year": "2008", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "14", "label": "January/February", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUzpzeAW", "doi": "10.1109/TVCG.2007.1068", "abstract": "Curved Planar Reformation (CPR) has proved to be a practical and widely used tool for the visualization of curved tubular structures within the human body. It has been useful in medical procedures involving the examination of blood vessels and the spine. However, it is more difficult to use it for large, tubular, structures such as the trachea and the colon because abnormalities may be smaller relative to the size of the structure and may not have such distinct density and shape characteristics.Our new approach improves on this situation by using volume rendering for hollow regions and standard CPR for the surrounding tissue. This effectively combines gray scale contextual information with detailed color information from the area of interest. The approach is successfully used with each of the standard CPR types and the resulting images are promising as an alternative to virtual endoscopy.Because the CPR and the volume rendering are tightly coupled, the projection method used has a significant effect on properties of the volume renderer such as distortion and isometry. We describe and compare the different CPR projection methods and how they affect the volume rendering process.A version of the algorithm is also presented which makes use of importance driven techniques; this ensures the users attention is always focused on the area of interest and also improves the speed of the algorithm.", "abstracts": [ { "abstractType": "Regular", "content": "Curved Planar Reformation (CPR) has proved to be a practical and widely used tool for the visualization of curved tubular structures within the human body. It has been useful in medical procedures involving the examination of blood vessels and the spine. However, it is more difficult to use it for large, tubular, structures such as the trachea and the colon because abnormalities may be smaller relative to the size of the structure and may not have such distinct density and shape characteristics.Our new approach improves on this situation by using volume rendering for hollow regions and standard CPR for the surrounding tissue. This effectively combines gray scale contextual information with detailed color information from the area of interest. The approach is successfully used with each of the standard CPR types and the resulting images are promising as an alternative to virtual endoscopy.Because the CPR and the volume rendering are tightly coupled, the projection method used has a significant effect on properties of the volume renderer such as distortion and isometry. We describe and compare the different CPR projection methods and how they affect the volume rendering process.A version of the algorithm is also presented which makes use of importance driven techniques; this ensures the users attention is always focused on the area of interest and also improves the speed of the algorithm.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Curved Planar Reformation (CPR) has proved to be a practical and widely used tool for the visualization of curved tubular structures within the human body. It has been useful in medical procedures involving the examination of blood vessels and the spine. However, it is more difficult to use it for large, tubular, structures such as the trachea and the colon because abnormalities may be smaller relative to the size of the structure and may not have such distinct density and shape characteristics.Our new approach improves on this situation by using volume rendering for hollow regions and standard CPR for the surrounding tissue. This effectively combines gray scale contextual information with detailed color information from the area of interest. The approach is successfully used with each of the standard CPR types and the resulting images are promising as an alternative to virtual endoscopy.Because the CPR and the volume rendering are tightly coupled, the projection method used has a significant effect on properties of the volume renderer such as distortion and isometry. We describe and compare the different CPR projection methods and how they affect the volume rendering process.A version of the algorithm is also presented which makes use of importance driven techniques; this ensures the users attention is always focused on the area of interest and also improves the speed of the algorithm.", "title": "Volumetric Curved Planar Reformation for Virtual Endoscopy", "normalizedTitle": "Volumetric Curved Planar Reformation for Virtual Endoscopy", "fno": "ttg2008010109", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Curved Planar Reformation", "Virtual Endoscopy", "Colon Screening" ], "authors": [ { "givenName": "David", "surname": "Williams", "fullName": "David Williams", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "S?ren", "surname": "Grimm", "fullName": "S?ren Grimm", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Ernesto", "surname": "Coto", "fullName": "Ernesto Coto", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Abdul", "surname": "Roudsari", "fullName": "Abdul Roudsari", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Haralambos", "surname": "Hatzakis", "fullName": "Haralambos Hatzakis", "affiliation": null, "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2008-01-01 00:00:00", "pubType": "trans", "pages": "109-119", "year": "2008", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/ieee-vis/2004/8788/0/87880385", "title": "The VesselGlyph: Focus & Context Visualization in CT-Angiography", "doi": null, "abstractUrl": "/proceedings-article/ieee-vis/2004/87880385/12OmNqFJhQU", "parentPublication": { "id": "proceedings/ieee-vis/2004/8788/0", "title": "Visualization Conference, IEEE", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icmcs/1999/0253/1/02539475", "title": "Construction of Virtual Environment for Endoscopy", "doi": null, "abstractUrl": "/proceedings-article/icmcs/1999/02539475/12OmNrAv3H7", "parentPublication": { "id": "proceedings/icmcs/1999/0253/1", "title": "Multimedia Computing and Systems, International Conference on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/ieee-vis/2003/2030/0/20300007", "title": "Advanced Curved Planar Reformation: Flattening of Vascular Structures", "doi": null, "abstractUrl": "/proceedings-article/ieee-vis/2003/20300007/12OmNwErpEV", "parentPublication": { "id": "proceedings/ieee-vis/2003/2030/0", "title": "Visualization Conference, IEEE", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/ieee-vis/2003/2030/0/20300005", "title": "Exploring Curved Anatomic Structures with Surface Sections", "doi": null, "abstractUrl": "/proceedings-article/ieee-vis/2003/20300005/12OmNyqiaVI", "parentPublication": { "id": "proceedings/ieee-vis/2003/2030/0", "title": "Visualization Conference, IEEE", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/ieee-vis/2002/7498/0/7498kanitsar", "title": "CPR - Curved Planar Reformation", "doi": null, "abstractUrl": "/proceedings-article/ieee-vis/2002/7498kanitsar/12OmNzSyCcj", "parentPublication": { "id": "proceedings/ieee-vis/2002/7498/0", "title": "Visualization Conference, IEEE", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/pg/1999/0293/0/02930092", "title": "A Scan Line Algorithm for Rendering Curved Tubular Objects", "doi": null, "abstractUrl": "/proceedings-article/pg/1999/02930092/12OmNzaQogu", "parentPublication": { "id": "proceedings/pg/1999/0293/0", "title": "Computer Graphics and Applications, Pacific Conference on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2013/12/ttg2013122858", "title": "Vessel Visualization using Curved Surface Reformation", "doi": null, "abstractUrl": "/journal/tg/2013/12/ttg2013122858/13rRUwIF6dS", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2009/06/ttg2009061235", "title": "Curve-Centric Volume Reformation for Comparative Visualization", "doi": null, "abstractUrl": "/journal/tg/2009/06/ttg2009061235/13rRUxlgxTg", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2010/06/ttg2010061396", "title": "Articulated Planar Reformation for Change Visualization in Small Animal Imaging", "doi": null, "abstractUrl": "/journal/tg/2010/06/ttg2010061396/13rRUygT7sy", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "ttg2008010097", "articleId": "13rRUwhpBE2", "__typename": "AdjacentArticleType" }, "next": { "fno": "ttg2008010120", "articleId": "13rRUxjQyho", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [], "articleVideos": [] }
{ "issue": { "id": "12OmNvAiSlz", "title": "January/February", "year": "2008", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "14", "label": "January/February", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUxjQyho", "doi": "10.1109/TVCG.2007.70412", "abstract": "Abstract—Information Visualization (InfoVis) is now an accepted and growing field but questions remain about the best uses for and the maturity of novel visualizations. Usability studies and controlled experiments are helpful but generalization is difficult. We believe that the systematic development of benchmarks will facilitate the comparison of techniques and help identify their strengths under different conditions. We were involved in the organization and management of three information visualization contests for the 2003, 2004 and 2005 IEEE Information Visualization Symposia, which requested teams to report on insights gained while exploring data. We give a summary of the state of the art of evaluation in information visualization, describe the three contests, summarize their results, discuss outcomes and lessons learned, and conjecture the future of visualization contests. All materials produced by the contests are archived in the Information Visualization Benchmark Repository.", "abstracts": [ { "abstractType": "Regular", "content": "Abstract—Information Visualization (InfoVis) is now an accepted and growing field but questions remain about the best uses for and the maturity of novel visualizations. Usability studies and controlled experiments are helpful but generalization is difficult. We believe that the systematic development of benchmarks will facilitate the comparison of techniques and help identify their strengths under different conditions. We were involved in the organization and management of three information visualization contests for the 2003, 2004 and 2005 IEEE Information Visualization Symposia, which requested teams to report on insights gained while exploring data. We give a summary of the state of the art of evaluation in information visualization, describe the three contests, summarize their results, discuss outcomes and lessons learned, and conjecture the future of visualization contests. All materials produced by the contests are archived in the Information Visualization Benchmark Repository.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Abstract—Information Visualization (InfoVis) is now an accepted and growing field but questions remain about the best uses for and the maturity of novel visualizations. Usability studies and controlled experiments are helpful but generalization is difficult. We believe that the systematic development of benchmarks will facilitate the comparison of techniques and help identify their strengths under different conditions. We were involved in the organization and management of three information visualization contests for the 2003, 2004 and 2005 IEEE Information Visualization Symposia, which requested teams to report on insights gained while exploring data. We give a summary of the state of the art of evaluation in information visualization, describe the three contests, summarize their results, discuss outcomes and lessons learned, and conjecture the future of visualization contests. All materials produced by the contests are archived in the Information Visualization Benchmark Repository.", "title": "Promoting Insight-Based Evaluation of Visualizations: From Contest to Benchmark Repository", "normalizedTitle": "Promoting Insight-Based Evaluation of Visualizations: From Contest to Benchmark Repository", "fno": "ttg2008010120", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Visualization", "Information", "Competition", "Contest", "Benchmark", "Repository", "Measure", "Metrics" ], "authors": [ { "givenName": "Catherine", "surname": "Plaisant", "fullName": "Catherine Plaisant", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Jean-Daniel", "surname": "Fekete", "fullName": "Jean-Daniel Fekete", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Georges", "surname": "Grinstein", "fullName": "Georges Grinstein", "affiliation": null, "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2008-01-01 00:00:00", "pubType": "trans", "pages": "120-134", "year": "2008", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/ieee-vis/1999/5897/0/58970015", "title": "Structured Spatial Domain Image and Data Comparison Metrics", "doi": null, "abstractUrl": "/proceedings-article/ieee-vis/1999/58970015/12OmNs0C9Px", "parentPublication": { "id": "proceedings/ieee-vis/1999/5897/0", "title": "Visualization Conference, IEEE", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icpads/1996/7267/0/72670472", "title": "A management information repository for distributed applications management", "doi": null, "abstractUrl": "/proceedings-article/icpads/1996/72670472/12OmNs4S8zu", "parentPublication": { "id": "proceedings/icpads/1996/7267/0", "title": "Parallel and Distributed Systems, International Conference on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/wi-iat/2008/3496/3/3496c287", "title": "Research on Automatic Acquiring of Chinese Synonyms from Wiki Repository", "doi": null, "abstractUrl": "/proceedings-article/wi-iat/2008/3496c287/12OmNwDj17h", "parentPublication": { "id": "proceedings/wi-iat/2008/3496/3", "title": "Web Intelligence and Intelligent Agent Technology, IEEE/WIC/ACM International Conference on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/ettandgrs/2008/3563/1/3563a163", "title": "Advanced Researches on Intelligent Spatial Decision Support System (ISDSS): A Combination of Model-Blade, Generalized Repository and GIS", "doi": null, "abstractUrl": "/proceedings-article/ettandgrs/2008/3563a163/12OmNwx3Q6T", "parentPublication": { "id": "proceedings/ettandgrs/2008/3563/1", "title": "Education Technology and Training &amp; Geoscience and Remote Sensing", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iv/2016/8942/0/8942a203", "title": "Promoting Insight: A Case Study of How to Incorporate Interaction in Existing Data Visualizations", "doi": null, "abstractUrl": "/proceedings-article/iv/2016/8942a203/12OmNx7G68T", "parentPublication": { "id": "proceedings/iv/2016/8942/0", "title": "2016 20th International Conference Information Visualisation (IV)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/hicss/2001/0981/9/09819065", "title": "An Active and Adaptive Reuse Repository System", "doi": null, "abstractUrl": "/proceedings-article/hicss/2001/09819065/12OmNzaQos5", "parentPublication": { "id": "proceedings/hicss/2001/0981/9", "title": "Proceedings of the 34th Annual Hawaii International Conference on System Sciences", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/aina/2017/6029/0/07920978", "title": "A Reuse-Based Approach to Promote the Adoption of Visualizations for Network Management Tasks", "doi": null, "abstractUrl": "/proceedings-article/aina/2017/07920978/12OmNzwZ6q3", "parentPublication": { "id": "proceedings/aina/2017/6029/0", "title": "2017 IEEE 31st International Conference on Advanced Information Networking and Applications (AINA)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/lt/2010/03/tlt2010030250", "title": "Ranking Metrics and Search Guidance for Learning Object Repository", "doi": null, "abstractUrl": "/journal/lt/2010/03/tlt2010030250/13rRUNvgz6o", "parentPublication": { "id": "trans/lt", "title": "IEEE Transactions on Learning Technologies", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "mags/cg/2011/05/mcg2011050006", "title": "2010 IEEE Visualization Contest Winner: Interactive Planning for Brain Tumor Resections", "doi": null, "abstractUrl": "/magazine/cg/2011/05/mcg2011050006/13rRUzp02il", "parentPublication": { "id": "mags/cg", "title": "IEEE Computer Graphics and Applications", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icws/2019/2717/0/271700a403", "title": "Promoting Higher Revenues for Both Crowdsourcer and Crowds in Crowdsourcing via Contest", "doi": null, "abstractUrl": "/proceedings-article/icws/2019/271700a403/1cTJtus6c12", "parentPublication": { "id": "proceedings/icws/2019/2717/0", "title": "2019 IEEE International Conference on Web Services (ICWS)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "ttg2008010109", "articleId": "13rRUzpzeAW", "__typename": "AdjacentArticleType" }, "next": { "fno": "ttg2008010135", "articleId": "13rRUyYBlgs", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [], "articleVideos": [] }
{ "issue": { "id": "12OmNvAiSlz", "title": "January/February", "year": "2008", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "14", "label": "January/February", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUyYBlgs", "doi": "10.1109/TVCG.2007.1058", "abstract": "Clip art is a simplified illustration form consisting of layered filled polygons or closed curves used to convey 3-D shape information in a 2-D vector graphics format. This paper focuses on the problem of direct conversion of smooth surfaces, ranging from the free-form shapes of art and design to the mathematical structures of geometry and topology, into a clip art form suitable for illustration use in books, papers and presentations.We show how to represent silhouette, shadow, gleam and other surface feature curves as the intersection of implicit surfaces, and derive equations for their efficient interrogation via particle chains. We further describe how to sort, orient, identify and fill the closed regions that overlay to form clip art. We demonstrate the results with numerous renderings used to illustrate the paper itself.", "abstracts": [ { "abstractType": "Regular", "content": "Clip art is a simplified illustration form consisting of layered filled polygons or closed curves used to convey 3-D shape information in a 2-D vector graphics format. This paper focuses on the problem of direct conversion of smooth surfaces, ranging from the free-form shapes of art and design to the mathematical structures of geometry and topology, into a clip art form suitable for illustration use in books, papers and presentations.We show how to represent silhouette, shadow, gleam and other surface feature curves as the intersection of implicit surfaces, and derive equations for their efficient interrogation via particle chains. We further describe how to sort, orient, identify and fill the closed regions that overlay to form clip art. We demonstrate the results with numerous renderings used to illustrate the paper itself.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Clip art is a simplified illustration form consisting of layered filled polygons or closed curves used to convey 3-D shape information in a 2-D vector graphics format. This paper focuses on the problem of direct conversion of smooth surfaces, ranging from the free-form shapes of art and design to the mathematical structures of geometry and topology, into a clip art form suitable for illustration use in books, papers and presentations.We show how to represent silhouette, shadow, gleam and other surface feature curves as the intersection of implicit surfaces, and derive equations for their efficient interrogation via particle chains. We further describe how to sort, orient, identify and fill the closed regions that overlay to form clip art. We demonstrate the results with numerous renderings used to illustrate the paper itself.", "title": "Clip Art Rendering of Smooth Isosurfaces", "normalizedTitle": "Clip Art Rendering of Smooth Isosurfaces", "fno": "ttg2008010135", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Particle Systems", "Non Photorealistic Rendering", "Line Art Drawing" ], "authors": [ { "givenName": "Matei", "surname": "Stroila", "fullName": "Matei Stroila", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Elmar", "surname": "Eisemann", "fullName": "Elmar Eisemann", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "John", "surname": "Hart", "fullName": "John Hart", "affiliation": null, "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2008-01-01 00:00:00", "pubType": "trans", "pages": "135-145", "year": "2008", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/vs-games/2011/4419/0/4419a176", "title": "On the Presentation of Byzantine Art in Virtual Environments", "doi": null, "abstractUrl": "/proceedings-article/vs-games/2011/4419a176/12OmNBU1jQn", "parentPublication": { "id": "proceedings/vs-games/2011/4419/0", "title": "Games and Virtual Worlds for Serious Applications, Conference in", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/ieee-vis/2000/6478/0/64780037", "title": "Volume Illustration: Non-Photorealistic Rendering of Volume Models", "doi": null, "abstractUrl": "/proceedings-article/ieee-vis/2000/64780037/12OmNC0y5FO", "parentPublication": { "id": "proceedings/ieee-vis/2000/6478/0", "title": "Visualization Conference, IEEE", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/ieee-vis/2002/7498/0/7498lu", "title": "Non-Photorealistic Volume Rendering Using Stippling Techniques", "doi": null, "abstractUrl": "/proceedings-article/ieee-vis/2002/7498lu/12OmNy9Prft", "parentPublication": { "id": "proceedings/ieee-vis/2002/7498/0", "title": "Visualization Conference, IEEE", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iccit/2008/3407/1/3407a925", "title": "Non-photorealistic Directional Line Draw Rendering", "doi": null, "abstractUrl": "/proceedings-article/iccit/2008/3407a925/12OmNyqzM2l", "parentPublication": { "id": "iccit/2008/3407/1", "title": "Convergence Information Technology, International Conference on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/1995/03/v0231", "title": "Line Art Rendering via a Coverage of Isoparametric Curves", "doi": null, "abstractUrl": "/journal/tg/1995/03/v0231/13rRUwbJD4B", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/wacv/2022/0915/0/091500a628", "title": "Shadow Art Revisited: A Differentiable Rendering Based Approach", "doi": null, "abstractUrl": "/proceedings-article/wacv/2022/091500a628/1B12RNuAqvS", "parentPublication": { "id": "proceedings/wacv/2022/0915/0", "title": "2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iv/2020/9134/0/913400a473", "title": "Event-based Viewing Tool for Learning Illustrations", "doi": null, "abstractUrl": "/proceedings-article/iv/2020/913400a473/1rSRbUnzQQ0", "parentPublication": { "id": "proceedings/iv/2020/9134/0", "title": "2020 24th International Conference Information Visualisation (IV)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iccea/2021/2616/0/261600a412", "title": "The Practice of Computer Graphic Illustration Art in Commercial Design", "doi": null, "abstractUrl": "/proceedings-article/iccea/2021/261600a412/1y4otZ36hJS", "parentPublication": { "id": "proceedings/iccea/2021/2616/0", "title": "2021 International Conference on Computer Engineering and Application (ICCEA)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/cvprw/2021/4899/0/489900d951", "title": "CLIP-Art: Contrastive Pre-training for Fine-Grained Art Classification", "doi": null, "abstractUrl": "/proceedings-article/cvprw/2021/489900d951/1yVA11rr77W", "parentPublication": { "id": "proceedings/cvprw/2021/4899/0", "title": "2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/cvprw/2021/4899/0/489900d941", "title": "Line Art Colorization with Concatenated Spatial Attention", "doi": null, "abstractUrl": "/proceedings-article/cvprw/2021/489900d941/1yVzYqkncJy", "parentPublication": { "id": "proceedings/cvprw/2021/4899/0", "title": "2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "ttg2008010120", "articleId": "13rRUxjQyho", "__typename": "AdjacentArticleType" }, "next": { "fno": "ttg2008010146", "articleId": "13rRUwh80H5", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [], "articleVideos": [] }
{ "issue": { "id": "12OmNvAiSlz", "title": "January/February", "year": "2008", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "14", "label": "January/February", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUwh80H5", "doi": "10.1109/TVCG.2007.1056", "abstract": "We use our hands to manipulate objects in our daily life. The hand is capable of accomplishing diverse tasks such as pointing, gripping, twisting and tearing. However, there is not much work that considers using the hand as input in distributed virtual environments (DVEs), in particular over the Internet. The main reasons are that the Internet suffers from high network latency, which affects interaction, and the hand has many degrees of freedom, which adds additional challenges to synchronizing the collaboration. In this paper, we propose a prediction method specifically designed for human hand motion to address the network latency problem in DVEs. Through a thorough analysis of finger motion, we have identified various finger motion constraints and we propose a constraint-based motion prediction method for hand motion. To reduce the average prediction error under high network latency, e.g., over the Internet, we further propose a revised dead reckoning scheme here. Our performance results show that the proposed prediction method produces a lower prediction error than some popular methods while the revised dead reckoning scheme produces a lower average prediction error than the traditional dead reckoning scheme, in particular at high network latency.", "abstracts": [ { "abstractType": "Regular", "content": "We use our hands to manipulate objects in our daily life. The hand is capable of accomplishing diverse tasks such as pointing, gripping, twisting and tearing. However, there is not much work that considers using the hand as input in distributed virtual environments (DVEs), in particular over the Internet. The main reasons are that the Internet suffers from high network latency, which affects interaction, and the hand has many degrees of freedom, which adds additional challenges to synchronizing the collaboration. In this paper, we propose a prediction method specifically designed for human hand motion to address the network latency problem in DVEs. Through a thorough analysis of finger motion, we have identified various finger motion constraints and we propose a constraint-based motion prediction method for hand motion. To reduce the average prediction error under high network latency, e.g., over the Internet, we further propose a revised dead reckoning scheme here. Our performance results show that the proposed prediction method produces a lower prediction error than some popular methods while the revised dead reckoning scheme produces a lower average prediction error than the traditional dead reckoning scheme, in particular at high network latency.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "We use our hands to manipulate objects in our daily life. The hand is capable of accomplishing diverse tasks such as pointing, gripping, twisting and tearing. However, there is not much work that considers using the hand as input in distributed virtual environments (DVEs), in particular over the Internet. The main reasons are that the Internet suffers from high network latency, which affects interaction, and the hand has many degrees of freedom, which adds additional challenges to synchronizing the collaboration. In this paper, we propose a prediction method specifically designed for human hand motion to address the network latency problem in DVEs. Through a thorough analysis of finger motion, we have identified various finger motion constraints and we propose a constraint-based motion prediction method for hand motion. To reduce the average prediction error under high network latency, e.g., over the Internet, we further propose a revised dead reckoning scheme here. Our performance results show that the proposed prediction method produces a lower prediction error than some popular methods while the revised dead reckoning scheme produces a lower average prediction error than the traditional dead reckoning scheme, in particular at high network latency.", "title": "Hand Motion Prediction for Distributed Virtual Environments", "normalizedTitle": "Hand Motion Prediction for Distributed Virtual Environments", "fno": "ttg2008010146", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Motion Prediction", "Hand Motion Prediction", "Hand Interaction", "Network Latency" ], "authors": [ { "givenName": "Addison", "surname": "Chan", "fullName": "Addison Chan", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Rynson", "surname": "Lau", "fullName": "Rynson Lau", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Lewis", "surname": "Li", "fullName": "Lewis Li", "affiliation": null, "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2008-01-01 00:00:00", "pubType": "trans", "pages": "146-159", "year": "2008", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/ds-rt/2015/7822/0/7822a108", "title": "A Path-Assisted Dead Reckoning Algorithm for Distributed Virtual Environments", "doi": null, "abstractUrl": "/proceedings-article/ds-rt/2015/7822a108/12OmNApcunK", "parentPublication": { "id": "proceedings/ds-rt/2015/7822/0", "title": "2015 IEEE/ACM 19th International Symposium on Distributed Simulation and Real Time Applications (DS-RT)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iros/1995/7108/1/71080193", "title": "Motion planning for hand-over between human and robot", "doi": null, "abstractUrl": "/proceedings-article/iros/1995/71080193/12OmNBEYzQC", "parentPublication": { "id": "proceedings/iros/1995/7108/1", "title": "Intelligent Robots and Systems, IEEE/RSJ International Conference on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/chinacom/2012/2698/0/06417440", "title": "Play patterns for path prediction in multiplayer online games", "doi": null, "abstractUrl": "/proceedings-article/chinacom/2012/06417440/12OmNwoPtB3", "parentPublication": { "id": "proceedings/chinacom/2012/2698/0", "title": "7th International Conference on Communications and Networking in China", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/humo/2000/0939/0/09390121", "title": "Modeling the constraints of human hand motion", "doi": null, "abstractUrl": "/proceedings-article/humo/2000/09390121/12OmNx7G63m", "parentPublication": { "id": "proceedings/humo/2000/0939/0", "title": "Human Motion, Workshop on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/wsc/2003/8131/2/01261536", "title": "Pre-reckoning algorithm for distributed virtual environments", "doi": null, "abstractUrl": "/proceedings-article/wsc/2003/01261536/12OmNynJMTo", "parentPublication": { "id": "proceedings/wsc/2003/8131/2", "title": "Proceedings of the 2003 Winter Simulation Conference", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icpads/2004/2152/0/21520445", "title": "Evaluation of a Pre-Reckoning Algorithm for Distributed Virtual Environments", "doi": null, "abstractUrl": "/proceedings-article/icpads/2004/21520445/12OmNzIUg0i", "parentPublication": { "id": "proceedings/icpads/2004/2152/0", "title": "Parallel and Distributed Systems, International Conference on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/fg/2008/2153/0/04813414", "title": "Using an adaptive VAR Model for motion prediction in 3D hand tracking", "doi": null, "abstractUrl": "/proceedings-article/fg/2008/04813414/12OmNzayNs5", "parentPublication": { "id": "proceedings/fg/2008/2153/0", "title": "2008 8th IEEE International Conference on Automatic Face & Gesture Recognition", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vr/2006/0224/0/02240073", "title": "Motion Prediction in Gesture-based Collaborative Design Environments", "doi": null, "abstractUrl": "/proceedings-article/vr/2006/02240073/12OmNzvz6Ka", "parentPublication": { "id": "proceedings/vr/2006/0224/0", "title": "IEEE Virtual Reality Conference (VR 2006)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tp/2002/08/i1061", "title": "Extraction of 2D Motion Trajectories and Its Application to Hand Gesture Recognition", "doi": null, "abstractUrl": "/journal/tp/2002/08/i1061/13rRUx0Pqqr", "parentPublication": { "id": "trans/tp", "title": "IEEE Transactions on Pattern Analysis & Machine Intelligence", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2012/05/ttg2012050729", "title": "Human Motion Retrieval from Hand-Drawn Sketch", "doi": null, "abstractUrl": "/journal/tg/2012/05/ttg2012050729/13rRUxjyX3X", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "ttg2008010135", "articleId": "13rRUyYBlgs", "__typename": "AdjacentArticleType" }, "next": { "fno": "ttg2008010160", "articleId": "13rRUy0qnLB", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [], "articleVideos": [] }
{ "issue": { "id": "12OmNvAiSlz", "title": "January/February", "year": "2008", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "14", "label": "January/February", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUy0qnLB", "doi": "10.1109/TVCG.2007.1057", "abstract": "In this paper we describe a novel 3-D subdivision strategy to extract the surface of binary image data. This iterative approach generates a series of surface meshes that capture different levels of detail of the underlying structure. At the highest level of detail, the resulting surface mesh generated by our approach uses only about 10% of the triangles in comparison to the marching cube algorithm (MC) even in settings were almost no image noise is present. Our approach also eliminates the so-called 'staircase effect' which voxel based algorithms like the MC are likely to show, particularly if non-uniformly sampled images are processed. Finally, we show how the presented algorithm can be parallelized by subdividing 3-D image space into rectilinear blocks of subimages. As the algorithm scales very well with an increasing number of processors in a multi-threaded setting, this approach is suited to process large image data sets of several gigabytes. Although the presented work is still computationally more expensive than simple voxel based algorithms, it produces fewer surface triangles while capturing the same level of detail, is more robust towards image noise and eliminates the above mentioned 'stair-case' effect in anisotropic settings. These properties make it particularly useful for biomedical applications, where these conditions are often encountered.", "abstracts": [ { "abstractType": "Regular", "content": "In this paper we describe a novel 3-D subdivision strategy to extract the surface of binary image data. This iterative approach generates a series of surface meshes that capture different levels of detail of the underlying structure. At the highest level of detail, the resulting surface mesh generated by our approach uses only about 10% of the triangles in comparison to the marching cube algorithm (MC) even in settings were almost no image noise is present. Our approach also eliminates the so-called 'staircase effect' which voxel based algorithms like the MC are likely to show, particularly if non-uniformly sampled images are processed. Finally, we show how the presented algorithm can be parallelized by subdividing 3-D image space into rectilinear blocks of subimages. As the algorithm scales very well with an increasing number of processors in a multi-threaded setting, this approach is suited to process large image data sets of several gigabytes. Although the presented work is still computationally more expensive than simple voxel based algorithms, it produces fewer surface triangles while capturing the same level of detail, is more robust towards image noise and eliminates the above mentioned 'stair-case' effect in anisotropic settings. These properties make it particularly useful for biomedical applications, where these conditions are often encountered.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "In this paper we describe a novel 3-D subdivision strategy to extract the surface of binary image data. This iterative approach generates a series of surface meshes that capture different levels of detail of the underlying structure. At the highest level of detail, the resulting surface mesh generated by our approach uses only about 10% of the triangles in comparison to the marching cube algorithm (MC) even in settings were almost no image noise is present. Our approach also eliminates the so-called 'staircase effect' which voxel based algorithms like the MC are likely to show, particularly if non-uniformly sampled images are processed. Finally, we show how the presented algorithm can be parallelized by subdividing 3-D image space into rectilinear blocks of subimages. As the algorithm scales very well with an increasing number of processors in a multi-threaded setting, this approach is suited to process large image data sets of several gigabytes. Although the presented work is still computationally more expensive than simple voxel based algorithms, it produces fewer surface triangles while capturing the same level of detail, is more robust towards image noise and eliminates the above mentioned 'stair-case' effect in anisotropic settings. These properties make it particularly useful for biomedical applications, where these conditions are often encountered.", "title": "A Parallelized Surface Extraction Algorithm for Large Binary Image Data Sets Based on an Adaptive 3-D Delaunay Subdivision Strategy", "normalizedTitle": "A Parallelized Surface Extraction Algorithm for Large Binary Image Data Sets Based on an Adaptive 3-D Delaunay Subdivision Strategy", "fno": "ttg2008010160", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Isosurface Extraction", "Adaptive Mesh Generation", "Delaunay Triangulation", "Parallel Computing" ], "authors": [ { "givenName": "YingLiang", "surname": "Ma", "fullName": "YingLiang Ma", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Kurt", "surname": "Saetzler", "fullName": "Kurt Saetzler", "affiliation": null, "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2008-01-01 00:00:00", "pubType": "trans", "pages": "160-172", "year": "2008", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/isvd/2010/4112/0/4112a215", "title": "Guaranteed Quality Tetrahedral Delaunay Meshing for Medical Images", "doi": null, "abstractUrl": "/proceedings-article/isvd/2010/4112a215/12OmNBOCWjK", "parentPublication": { "id": "proceedings/isvd/2010/4112/0", "title": "2010 International Symposium on Voronoi Diagrams in Science and Engineering", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/apdc/1997/7876/0/78760131", "title": "An Improved Parallel Algorithm for Delaunay Triangulation on Distributed Memory Parallel Computers", "doi": null, "abstractUrl": "/proceedings-article/apdc/1997/78760131/12OmNBTawsE", "parentPublication": { "id": "proceedings/apdc/1997/7876/0", "title": "Advances in Parallel and Distributed Computing Conference", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icseng/2011/4495/0/4495a194", "title": "Ear-Slicing and Quality Triangulation", "doi": null, "abstractUrl": "/proceedings-article/icseng/2011/4495a194/12OmNCcbEcW", "parentPublication": { "id": "proceedings/icseng/2011/4495/0", "title": "Systems Engineering, International Conference on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/dcc/2000/0592/0/05920410", "title": "Piecewise Linear Image Coding Using Surface Triangulation and Geometric Compression", "doi": null, "abstractUrl": "/proceedings-article/dcc/2000/05920410/12OmNCfSqRV", "parentPublication": { "id": "proceedings/dcc/2000/0592/0", "title": "Data Compression Conference", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/ispa/2011/4428/0/4428a052", "title": "A Parallel 3D Delaunay Triangulation Method", "doi": null, "abstractUrl": "/proceedings-article/ispa/2011/4428a052/12OmNrIaehr", "parentPublication": { "id": "proceedings/ispa/2011/4428/0", "title": "International Symposium on Parallel and Distributed Processing with Applications", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iciis/1999/0446/0/04460452", "title": "Fingerprint Identification Using Delaunay Triangulation", "doi": null, "abstractUrl": "/proceedings-article/iciis/1999/04460452/12OmNwNwzFJ", "parentPublication": { "id": "proceedings/iciis/1999/0446/0", "title": "Information, Intelligence, and Systems, International Conference on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/isvd/2011/4483/0/4483a039", "title": "Isotropic Mesh Simplification by Evolving the Geodesic Delaunay Triangulation", "doi": null, "abstractUrl": "/proceedings-article/isvd/2011/4483a039/12OmNwwd2VI", "parentPublication": { "id": "proceedings/isvd/2011/4483/0", "title": "2011 Eighth International Symposium on Voronoi Diagrams in Science and Engineering", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icpads/2002/1760/0/17600571", "title": "A Parallel Divide-and-Conquer Scheme for Delaunay Triangulation", "doi": null, "abstractUrl": "/proceedings-article/icpads/2002/17600571/12OmNyxFKdi", "parentPublication": { "id": "proceedings/icpads/2002/1760/0", "title": "Proceedings of the Ninth International Conference on Parallel and Distributed Systems", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/wcse/2010/4303/1/4303a187", "title": "Fast Delaunay Triangulation and Voronoi Diagram Generation on the Sphere", "doi": null, "abstractUrl": "/proceedings-article/wcse/2010/4303a187/12OmNzDehe0", "parentPublication": { "id": "wcse/2010/4303/1", "title": "2010 Second World Congress on Software Engineering", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/1997/03/v0215", "title": "On Approximating Contours of the Piecewise Trilinear Interpolant Using Triangular Rational-Quadratic Bézier Patches", "doi": null, "abstractUrl": "/journal/tg/1997/03/v0215/13rRUNvyaeP", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "ttg2008010146", "articleId": "13rRUwh80H5", "__typename": "AdjacentArticleType" }, "next": { "fno": "ttg2008010173", "articleId": "13rRUygT7f3", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [], "articleVideos": [] }
{ "issue": { "id": "12OmNvAiSlz", "title": "January/February", "year": "2008", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "14", "label": "January/February", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUygT7f3", "doi": "10.1109/TVCG.2007.70427", "abstract": "We present a psychology-inspired approach for generating a character' s anticipation of and response to an impending head or upper body impact. Protective anticipatory movement is built upon several actions that have been identified in the psychology literature as response mechanisms in monkeys and in humans. These actions are parameterized by a model of the approaching object (the threat) and are defined as procedural rules. We present a hybrid forward and inverse kinematic blending technique to guide the character to the pose that results from these rules while maintaining properties of a balanced posture as well as characteristics of the behavior just prior to the interaction. In our case, these characteristics are determined by a motion capture sequence. We combine our anticipation model with a physically-based dynamic response to produce animations where a character anticipates an impact before collision and reacts to the contact, physically, after the collision. We present a variety of examples including threats that vary in approach direction, size and speed.", "abstracts": [ { "abstractType": "Regular", "content": "We present a psychology-inspired approach for generating a character' s anticipation of and response to an impending head or upper body impact. Protective anticipatory movement is built upon several actions that have been identified in the psychology literature as response mechanisms in monkeys and in humans. These actions are parameterized by a model of the approaching object (the threat) and are defined as procedural rules. We present a hybrid forward and inverse kinematic blending technique to guide the character to the pose that results from these rules while maintaining properties of a balanced posture as well as characteristics of the behavior just prior to the interaction. In our case, these characteristics are determined by a motion capture sequence. We combine our anticipation model with a physically-based dynamic response to produce animations where a character anticipates an impact before collision and reacts to the contact, physically, after the collision. We present a variety of examples including threats that vary in approach direction, size and speed.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "We present a psychology-inspired approach for generating a character' s anticipation of and response to an impending head or upper body impact. Protective anticipatory movement is built upon several actions that have been identified in the psychology literature as response mechanisms in monkeys and in humans. These actions are parameterized by a model of the approaching object (the threat) and are defined as procedural rules. We present a hybrid forward and inverse kinematic blending technique to guide the character to the pose that results from these rules while maintaining properties of a balanced posture as well as characteristics of the behavior just prior to the interaction. In our case, these characteristics are determined by a motion capture sequence. We combine our anticipation model with a physically-based dynamic response to produce animations where a character anticipates an impact before collision and reacts to the contact, physically, after the collision. We present a variety of examples including threats that vary in approach direction, size and speed.", "title": "Psychologically Inspired Anticipation and Dynamic Response for Impacts to the Head and Upper Body", "normalizedTitle": "Psychologically Inspired Anticipation and Dynamic Response for Impacts to the Head and Upper Body", "fno": "ttg2008010173", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Animation", "Motion Capture", "Physically Based Modeling", "Kinematics And Dynamics" ], "authors": [ { "givenName": "Ronald", "surname": "Metoyer", "fullName": "Ronald Metoyer", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Victor", "surname": "Zordan", "fullName": "Victor Zordan", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Benjamin", "surname": "Hermens", "fullName": "Benjamin Hermens", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Chun-Chi", "surname": "Wu", "fullName": "Chun-Chi Wu", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Marc", "surname": "Soriano", "fullName": "Marc Soriano", "affiliation": null, "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2008-01-01 00:00:00", "pubType": "trans", "pages": "173-185", "year": "2008", "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/cgi/2003/1946/0/19460266", "title": "An inverse kinematics method for 3D figures with motion data", "doi": null, "abstractUrl": "/proceedings-article/cgi/2003/19460266/12OmNwwd2S9", "parentPublication": { "id": "proceedings/cgi/2003/1946/0", "title": "Computer Graphics International Conference", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vsmm/1997/8150/0/81500100", "title": "Animated Interactive Fiction: Storytelling by a Conversational Virtual Actor", "doi": null, "abstractUrl": "/proceedings-article/vsmm/1997/81500100/12OmNxwWoBK", "parentPublication": { "id": "proceedings/vsmm/1997/8150/0", "title": "Virtual Systems and MultiMedia, International Conference on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iv/2005/2397/0/23970571", "title": "Motion Data Correction and Extrapolation Using Physical Constraints", "doi": null, "abstractUrl": "/proceedings-article/iv/2005/23970571/12OmNyoAAc4", "parentPublication": { "id": "proceedings/iv/2005/2397/0", "title": "Ninth International Conference on Information Visualisation (IV'05)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icvgip/2008/3476/0/3476a063", "title": "Explosion Simulation Using Compressible Fluids", "doi": null, "abstractUrl": "/proceedings-article/icvgip/2008/3476a063/12OmNz5JBRO", "parentPublication": { "id": "proceedings/icvgip/2008/3476/0", "title": "Computer Vision, Graphics &amp; Image Processing, Indian Conference on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "mags/cg/2011/04/05934840", "title": "Direct Control of Simulated Nonhuman Characters", "doi": null, "abstractUrl": "/magazine/cg/2011/04/05934840/13rRUILtJtD", "parentPublication": { "id": "mags/cg", "title": "IEEE Computer Graphics and Applications", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "mags/cg/2011/04/mcg2011040056", "title": "Direct Control of Simulated Nonhuman Characters", "doi": null, "abstractUrl": "/magazine/cg/2011/04/mcg2011040056/13rRUwInv93", "parentPublication": { "id": "mags/cg", "title": "IEEE Computer Graphics and Applications", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2010/02/ttg2010020325", "title": "Real-Time Physics-Based 3D Biped Character Animation Using an Inverted Pendulum Model", "doi": null, "abstractUrl": "/journal/tg/2010/02/ttg2010020325/13rRUwdIOUF", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "mags/cg/2011/04/mcg2011040045", "title": "Practical Character Physics for Animators", "doi": null, "abstractUrl": "/magazine/cg/2011/04/mcg2011040045/13rRUwjoNzG", "parentPublication": { "id": "mags/cg", "title": "IEEE Computer Graphics and Applications", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2008/01/ttg2008010037", "title": "Impulse-Based Control of Joints and Muscles", "doi": null, "abstractUrl": "/journal/tg/2008/01/ttg2008010037/13rRUxD9gXz", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "ttg2008010160", "articleId": "13rRUy0qnLB", "__typename": "AdjacentArticleType" }, "next": { "fno": "ttg2008010186", "articleId": "13rRUyY28Yn", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [], "articleVideos": [] }
{ "issue": { "id": "12OmNvAiSlz", "title": "January/February", "year": "2008", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "14", "label": "January/February", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUyY28Yn", "doi": "10.1109/TVCG.2007.70406", "abstract": "Abstract—Visual data comprise of multi-scale and inhomogeneous signals. In this paper, we exploit these characteristics and develop a compact data representation technique based on a hierarchical tensor-based transformation. In this technique, an original multi-dimensional dataset is transformed into a hierarchy of signals to expose its multi-scale structures. The signal at each level of the hierarchy is further divided into a number of smaller tensors to expose its spatially inhomogeneous structures. These smaller tensors are further transformed and pruned using a tensor approximation technique. Our hierarchical tensor approximation supports progressive transmission and partial decompression. Experimental results indicate that our technique can achieve higher compression ratios and quality than previous methods, including wavelet transforms, wavelet packet transforms, and single-level tensor approximation. We have successfully applied our technique to multiple tasks involving multi-dimensional visual data, including medical and scientific data visualization, data-driven rendering and texture synthesis.", "abstracts": [ { "abstractType": "Regular", "content": "Abstract—Visual data comprise of multi-scale and inhomogeneous signals. In this paper, we exploit these characteristics and develop a compact data representation technique based on a hierarchical tensor-based transformation. In this technique, an original multi-dimensional dataset is transformed into a hierarchy of signals to expose its multi-scale structures. The signal at each level of the hierarchy is further divided into a number of smaller tensors to expose its spatially inhomogeneous structures. These smaller tensors are further transformed and pruned using a tensor approximation technique. Our hierarchical tensor approximation supports progressive transmission and partial decompression. Experimental results indicate that our technique can achieve higher compression ratios and quality than previous methods, including wavelet transforms, wavelet packet transforms, and single-level tensor approximation. We have successfully applied our technique to multiple tasks involving multi-dimensional visual data, including medical and scientific data visualization, data-driven rendering and texture synthesis.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Abstract—Visual data comprise of multi-scale and inhomogeneous signals. In this paper, we exploit these characteristics and develop a compact data representation technique based on a hierarchical tensor-based transformation. In this technique, an original multi-dimensional dataset is transformed into a hierarchy of signals to expose its multi-scale structures. The signal at each level of the hierarchy is further divided into a number of smaller tensors to expose its spatially inhomogeneous structures. These smaller tensors are further transformed and pruned using a tensor approximation technique. Our hierarchical tensor approximation supports progressive transmission and partial decompression. Experimental results indicate that our technique can achieve higher compression ratios and quality than previous methods, including wavelet transforms, wavelet packet transforms, and single-level tensor approximation. We have successfully applied our technique to multiple tasks involving multi-dimensional visual data, including medical and scientific data visualization, data-driven rendering and texture synthesis.", "title": "Hierarchical Tensor Approximation of Multi-Dimensional Visual Data", "normalizedTitle": "Hierarchical Tensor Approximation of Multi-Dimensional Visual Data", "fno": "ttg2008010186", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Multilinear Models", "Multidimensional Image Compression", "Hierarchical Transformation", "Tensor Ensemble Approximation", "Progressive Transmission", "Texture Synthesis" ], "authors": [ { "givenName": "Qing", "surname": "Wu", "fullName": "Qing Wu", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Tian", "surname": "Xia", "fullName": "Tian Xia", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Chun", "surname": "Chen", "fullName": "Chun Chen", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Hsueh-Yi Sean", "surname": "Lin", "fullName": "Hsueh-Yi Sean Lin", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Hongcheng", "surname": "Wang", "fullName": "Hongcheng Wang", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Yizhou", "surname": "Yu", "fullName": "Yizhou Yu", "affiliation": null, "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2008-01-01 00:00:00", "pubType": "trans", "pages": "186-199", "year": "2008", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/icdm/2011/4408/0/4408a447", "title": "Boolean Tensor Factorizations", "doi": null, "abstractUrl": "/proceedings-article/icdm/2011/4408a447/12OmNAWH9IW", "parentPublication": { "id": "proceedings/icdm/2011/4408/0", "title": "2011 IEEE 11th International Conference on Data Mining", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/ieee-vis/2005/2766/0/27660002", "title": "Exploring 2D Tensor Fields Using Stress Nets", "doi": null, "abstractUrl": "/proceedings-article/ieee-vis/2005/27660002/12OmNBCZnRL", "parentPublication": { "id": "proceedings/ieee-vis/2005/2766/0", "title": "Visualization Conference, IEEE", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/cvprw/2006/2646/0/26460086", "title": "Robust Tensor Splines for Approximation of Diffusion Tensor MRI Data", "doi": null, "abstractUrl": "/proceedings-article/cvprw/2006/26460086/12OmNC8dgcX", "parentPublication": { "id": "proceedings/cvprw/2006/2646/0", "title": "2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icdm/2008/3502/0/3502a363", "title": "Scalable Tensor Decompositions for Multi-aspect Data Mining", "doi": null, "abstractUrl": "/proceedings-article/icdm/2008/3502a363/12OmNCfAPCM", "parentPublication": { "id": "proceedings/icdm/2008/3502/0", "title": "2008 Eighth IEEE International Conference on Data Mining", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/ccc/2011/4411/0/4411a283", "title": "Tensor Rank: Some Lower and Upper Bounds", "doi": null, "abstractUrl": "/proceedings-article/ccc/2011/4411a283/12OmNwE9Ovg", "parentPublication": { "id": "proceedings/ccc/2011/4411/0", "title": "2011 IEEE 26th Annual Conference on Computational Complexity", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/ieee-vis/2005/2766/0/27660004", "title": "HOT- Lines: Tracking Lines in Higher Order Tensor Fields", "doi": null, "abstractUrl": "/proceedings-article/ieee-vis/2005/27660004/12OmNwMXnqd", "parentPublication": { "id": "proceedings/ieee-vis/2005/2766/0", "title": "Visualization Conference, IEEE", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icpr/2010/4109/0/4109c600", "title": "Object Tracking by Structure Tensor Analysis", "doi": null, "abstractUrl": "/proceedings-article/icpr/2010/4109c600/12OmNx7ouSf", "parentPublication": { "id": "proceedings/icpr/2010/4109/0", "title": "Pattern Recognition, International Conference on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icpr/2010/4109/0/4109d372", "title": "Robust Color Image Segmentation through Tensor Voting", "doi": null, "abstractUrl": "/proceedings-article/icpr/2010/4109d372/12OmNxwENL9", "parentPublication": { "id": "proceedings/icpr/2010/4109/0", "title": "Pattern Recognition, International Conference on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/ieee-vis/1997/8262/0/82620059", "title": "Singularities in nonuniform tensor fields", "doi": null, "abstractUrl": "/proceedings-article/ieee-vis/1997/82620059/12OmNzFMFiX", "parentPublication": { "id": "proceedings/ieee-vis/1997/8262/0", "title": "Visualization Conference, IEEE", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/ieee-vis/2004/8788/0/87880123", "title": "Physically Based Methods for Tensor Field Visualization", "doi": null, "abstractUrl": "/proceedings-article/ieee-vis/2004/87880123/12OmNzTppFk", "parentPublication": { "id": "proceedings/ieee-vis/2004/8788/0", "title": "Visualization Conference, IEEE", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "ttg2008010173", "articleId": "13rRUygT7f3", "__typename": "AdjacentArticleType" }, "next": { "fno": "ttg2008010200", "articleId": "13rRUxly9dN", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, 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{ "issue": { "id": "12OmNvAiSlz", "title": "January/February", "year": "2008", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "14", "label": "January/February", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUxly9dN", "doi": "10.1109/TVCG.2007.70625", "abstract": "This paper presents a sharpness-based method for hole-filling that can repair a 3D model such that its shape conforms to that of the original model. The method involves two processes: interpolation-based hole-filling, which produces an initial repaired model; and post-processing, which adjusts the shape of the initial repaired model to conform to that of the original model. In the interpolation-based hole-filling process, a surface interpolation algorithm based on the radial basis function creates a smooth implicit surface that fills the hole. Then, a regularized marching tetrahedral algorithm is used to triangulate the implicit surface. Finally a stitching and regulating strategy is applied to the surface patch and its neighboring boundary polygon meshes to produce an initial repaired mesh model, which is a regular mesh model suitable for post-processing. During post-processing, a sharpness dependent filtering algorithm is applied to the initial repaired model. This is an iterative procedure whereby each iteration step adjusts the face normal associated with each meshed polygon to recover the sharp features hidden in the repaired model. The experiment results demonstrate that the method is effective in repairing incomplete 3D mesh models.", "abstracts": [ { "abstractType": "Regular", "content": "This paper presents a sharpness-based method for hole-filling that can repair a 3D model such that its shape conforms to that of the original model. The method involves two processes: interpolation-based hole-filling, which produces an initial repaired model; and post-processing, which adjusts the shape of the initial repaired model to conform to that of the original model. In the interpolation-based hole-filling process, a surface interpolation algorithm based on the radial basis function creates a smooth implicit surface that fills the hole. Then, a regularized marching tetrahedral algorithm is used to triangulate the implicit surface. Finally a stitching and regulating strategy is applied to the surface patch and its neighboring boundary polygon meshes to produce an initial repaired mesh model, which is a regular mesh model suitable for post-processing. During post-processing, a sharpness dependent filtering algorithm is applied to the initial repaired model. This is an iterative procedure whereby each iteration step adjusts the face normal associated with each meshed polygon to recover the sharp features hidden in the repaired model. The experiment results demonstrate that the method is effective in repairing incomplete 3D mesh models.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "This paper presents a sharpness-based method for hole-filling that can repair a 3D model such that its shape conforms to that of the original model. The method involves two processes: interpolation-based hole-filling, which produces an initial repaired model; and post-processing, which adjusts the shape of the initial repaired model to conform to that of the original model. In the interpolation-based hole-filling process, a surface interpolation algorithm based on the radial basis function creates a smooth implicit surface that fills the hole. Then, a regularized marching tetrahedral algorithm is used to triangulate the implicit surface. Finally a stitching and regulating strategy is applied to the surface patch and its neighboring boundary polygon meshes to produce an initial repaired mesh model, which is a regular mesh model suitable for post-processing. During post-processing, a sharpness dependent filtering algorithm is applied to the initial repaired model. This is an iterative procedure whereby each iteration step adjusts the face normal associated with each meshed polygon to recover the sharp features hidden in the repaired model. The experiment results demonstrate that the method is effective in repairing incomplete 3D mesh models.", "title": "A Sharpness-Dependent Filter for Recovering Sharp Features in Repaired 3D Mesh Models", "normalizedTitle": "A Sharpness-Dependent Filter for Recovering Sharp Features in Repaired 3D Mesh Models", "fno": "ttg2008010200", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Feature Representation", "Filtering", "Geometric Correction", "Surface Fitting", "Mesh Repair" ], "authors": [ { "givenName": "Chun-Yen", "surname": "Chen", "fullName": "Chun-Yen Chen", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Kuo-Young", "surname": "Cheng", "fullName": "Kuo-Young Cheng", "affiliation": null, "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2008-01-01 00:00:00", "pubType": "trans", "pages": "200-212", "year": "2008", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/3dpvt/2006/2825/0/04155795", "title": "Automatic Hole-Filling of Triangular Meshes Using Local Radial Basis Function", "doi": null, "abstractUrl": "/proceedings-article/3dpvt/2006/04155795/12OmNApu5sy", "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/icmtma/2009/3583/1/3583a568", "title": "A New Modeling Method on Skull Defect Repair", "doi": null, "abstractUrl": "/proceedings-article/icmtma/2009/3583a568/12OmNBBzokm", "parentPublication": { "id": "proceedings/icmtma/2009/3583/3", "title": "2009 International Conference on Measuring Technology and Mechatronics Automation", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icme/2004/8603/1/01394143", "title": "Regular 3D mesh reconstruction based on cylindrical mapping", "doi": null, "abstractUrl": "/proceedings-article/icme/2004/01394143/12OmNCeaPSH", "parentPublication": { "id": "proceedings/icme/2004/8603/1", "title": "2004 IEEE International Conference on Multimedia and Expo (ICME)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/aici/2010/4225/3/4225c306", "title": "An Integrated Approach to Filling Holes in Meshes", "doi": null, "abstractUrl": "/proceedings-article/aici/2010/4225c306/12OmNvEhg14", "parentPublication": { "id": "proceedings/aici/2010/4225/3", "title": "Artificial Intelligence and Computational Intelligence, International Conference on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/cgiv/2005/2392/0/23920447", "title": "Surface Modelling Using Fourth Order Geometric Flows", "doi": null, "abstractUrl": "/proceedings-article/cgiv/2005/23920447/12OmNwswg2T", "parentPublication": { "id": "proceedings/cgiv/2005/2392/0", "title": "International Conference on Computer Graphics, Imaging and Visualization (CGIV'05)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tc/1985/11/01676541", "title": "Further Comments on \"The Reliability of Periodically Repaired n ?l/n Parallel Redundant Systems\"", "doi": null, "abstractUrl": "/journal/tc/1985/11/01676541/13rRUILtJkO", "parentPublication": { "id": "trans/tc", "title": "IEEE Transactions on Computers", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tc/1983/06/01676284", "title": "The Reliability of Periodically Repaired n - I/n Parallel Redundant Systems", "doi": null, "abstractUrl": "/journal/tc/1983/06/01676284/13rRUx0xPuo", "parentPublication": { "id": "trans/tc", "title": "IEEE Transactions on Computers", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2006/04/v0629", "title": "Bilateral Recovering of Sharp Edges on Feature-Insensitive Sampled Meshes", "doi": null, "abstractUrl": "/journal/tg/2006/04/v0629/13rRUynHuiY", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icvrv/2017/2636/0/263600a061", "title": "Point Cloud Hole Filling Based on Feature Lines Extraction", "doi": null, "abstractUrl": "/proceedings-article/icvrv/2017/263600a061/1ap5xjYpSZa", "parentPublication": { "id": "proceedings/icvrv/2017/2636/0", "title": "2017 International Conference on Virtual Reality and Visualization (ICVRV)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icvrv/2017/2636/0/263600a079", "title": "A Repair Method of Point Cloud with Big Hole", "doi": null, "abstractUrl": "/proceedings-article/icvrv/2017/263600a079/1ap5yUFqLXW", "parentPublication": { "id": "proceedings/icvrv/2017/2636/0", "title": "2017 International Conference on Virtual Reality and Visualization (ICVRV)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "ttg2008010186", "articleId": "13rRUyY28Yn", "__typename": "AdjacentArticleType" }, "next": { "fno": "ttg2008010213", "articleId": "13rRUwvBy8P", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [], "articleVideos": [] }
{ "issue": { "id": "12OmNvAiSlz", "title": "January/February", "year": "2008", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "14", "label": "January/February", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUwvBy8P", "doi": "10.1109/TVCG.2007.1054", "abstract": "This survey reviews the recent advances in linear variational mesh deformation techniques. These methods were developed for editing detailed high-resolution meshes, like those produced by scanning real-world objects. The challenge of manipulating such complex surfaces is three-fold: the deformation technique has to be sufficiently fast, robust, and intuitive and easy to control to be useful for interactive applications. An intuitive, and thus predictable, deformation tool should provide physically plausible and aesthetically pleasing surface deformations, which in particular requires its geometric details to be preserved. The methods we survey generally formulate surface deformation as a global variational optimization problem that addresses the differential properties of the edited surface. Efficiency and robustness are achieved by linearizing the underlying objective functional, such that the global optimization amounts to solving a sparse linear system of equations. We review the different deformation energies and detail preservation techniques that were proposed in the recent years, together with the various techniques to rectify the linearization artifacts. Our goal is to provide the reader with a systematic classification and comparative description of the different techniques, revealing the strengths and weaknesses of each approach in common editing scenarios.", "abstracts": [ { "abstractType": "Regular", "content": "This survey reviews the recent advances in linear variational mesh deformation techniques. These methods were developed for editing detailed high-resolution meshes, like those produced by scanning real-world objects. The challenge of manipulating such complex surfaces is three-fold: the deformation technique has to be sufficiently fast, robust, and intuitive and easy to control to be useful for interactive applications. An intuitive, and thus predictable, deformation tool should provide physically plausible and aesthetically pleasing surface deformations, which in particular requires its geometric details to be preserved. The methods we survey generally formulate surface deformation as a global variational optimization problem that addresses the differential properties of the edited surface. Efficiency and robustness are achieved by linearizing the underlying objective functional, such that the global optimization amounts to solving a sparse linear system of equations. We review the different deformation energies and detail preservation techniques that were proposed in the recent years, together with the various techniques to rectify the linearization artifacts. Our goal is to provide the reader with a systematic classification and comparative description of the different techniques, revealing the strengths and weaknesses of each approach in common editing scenarios.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "This survey reviews the recent advances in linear variational mesh deformation techniques. These methods were developed for editing detailed high-resolution meshes, like those produced by scanning real-world objects. The challenge of manipulating such complex surfaces is three-fold: the deformation technique has to be sufficiently fast, robust, and intuitive and easy to control to be useful for interactive applications. An intuitive, and thus predictable, deformation tool should provide physically plausible and aesthetically pleasing surface deformations, which in particular requires its geometric details to be preserved. The methods we survey generally formulate surface deformation as a global variational optimization problem that addresses the differential properties of the edited surface. Efficiency and robustness are achieved by linearizing the underlying objective functional, such that the global optimization amounts to solving a sparse linear system of equations. We review the different deformation energies and detail preservation techniques that were proposed in the recent years, together with the various techniques to rectify the linearization artifacts. Our goal is to provide the reader with a systematic classification and comparative description of the different techniques, revealing the strengths and weaknesses of each approach in common editing scenarios.", "title": "On Linear Variational Surface Deformation Methods", "normalizedTitle": "On Linear Variational Surface Deformation Methods", "fno": "ttg2008010213", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Mesh Editing", "Linear Optimization", "Discrete Differential Operators" ], "authors": [ { "givenName": "Mario", "surname": "Botsch", "fullName": "Mario Botsch", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Olga", "surname": "Sorkine", "fullName": "Olga Sorkine", "affiliation": null, "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2008-01-01 00:00:00", "pubType": "trans", "pages": "213-230", "year": "2008", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/cadgraphics/2011/4497/0/4497a130", "title": "Tetrahedral Mesh Editing with Local Feature Manipulations", "doi": null, "abstractUrl": "/proceedings-article/cadgraphics/2011/4497a130/12OmNBTJIN5", "parentPublication": { "id": "proceedings/cadgraphics/2011/4497/0", "title": "Computer-Aided Design and Computer Graphics, International Conference on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/smi/2006/2591/0/25910021", "title": "Length Constrained Multiresolution Deformation for Surface Wrinkling", "doi": null, "abstractUrl": "/proceedings-article/smi/2006/25910021/12OmNqJ8tjd", "parentPublication": { "id": "proceedings/smi/2006/2591/0", "title": "IEEE International Conference on Shape Modeling and Applications 2006", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/smi/2004/2075/0/20750119", "title": "Detail-Preserving Variational Surface Design with Multiresolution Constraints", "doi": null, "abstractUrl": "/proceedings-article/smi/2004/20750119/12OmNvTTcaV", "parentPublication": { "id": "proceedings/smi/2004/2075/0", "title": "Proceedings. Shape Modeling International 2004", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icma/2010/4293/0/4293a087", "title": "Constraints Based Deformation", "doi": null, "abstractUrl": "/proceedings-article/icma/2010/4293a087/12OmNwE9ODE", "parentPublication": { "id": "proceedings/icma/2010/4293/0", "title": "2010 International Conference on Manufacturing Automation", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icis/2009/3641/0/3641b068", "title": "A Framework for Real-time Local Free-Form Deformation", "doi": null, "abstractUrl": "/proceedings-article/icis/2009/3641b068/12OmNweBUIN", "parentPublication": { "id": "proceedings/icis/2009/3641/0", "title": "Computer and Information Science, ACIS International Conference on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icvgip/2008/3476/0/3476a055", "title": "Multi-scale Method for Adaptive Mesh Editing Based on Rigidity Estimation", "doi": null, "abstractUrl": "/proceedings-article/icvgip/2008/3476a055/12OmNwx3Qao", "parentPublication": { "id": "proceedings/icvgip/2008/3476/0", "title": "Computer Vision, Graphics &amp; Image Processing, Indian Conference on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/cw/2003/1922/0/19220206", "title": "Detail-Preserving Variational Design of B-Spline Curves and Surfaces", "doi": null, "abstractUrl": "/proceedings-article/cw/2003/19220206/12OmNyOq52I", "parentPublication": { "id": "proceedings/cw/2003/1922/0", "title": "Proceedings. 2003 International Conference on Cyberworlds", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/cvmp/2011/4621/0/4621a148", "title": "Space-time Editing of 3D Video Sequences", "doi": null, "abstractUrl": "/proceedings-article/cvmp/2011/4621a148/12OmNzGDsMm", "parentPublication": { "id": "proceedings/cvmp/2011/4621/0", "title": "2011 Conference for Visual Media Production", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2009/03/ttg2009030518", "title": "Quasi-Developable Mesh Surface Interpolation via Mesh Deformation", "doi": null, "abstractUrl": "/journal/tg/2009/03/ttg2009030518/13rRUxjQybN", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tp/2022/10/09444875", "title": "Variational Autoencoders for Localized Mesh Deformation Component Analysis", "doi": null, "abstractUrl": "/journal/tp/2022/10/09444875/1u51uvab1eM", "parentPublication": { "id": "trans/tp", "title": "IEEE Transactions on Pattern Analysis & Machine Intelligence", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "ttg2008010200", "articleId": "13rRUxly9dN", "__typename": "AdjacentArticleType" }, "next": { "fno": "ttg2008010231", "articleId": "13rRUILLkvj", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [], "articleVideos": [] }
{ "issue": { "id": "12OmNvAiSlz", "title": "January/February", "year": "2008", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "14", "label": "January/February", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUILLkvj", "doi": "10.1109/TVCG.2007.70416", "abstract": "Two methods have been used extensively to model resting contact for rigid body simulation. The first approach, the penalty method, applies virtual springs to surfaces in contact to minimize interpenetration. This method, as typically implemented, results in oscillatory behavior and considerable penetration. The second approach, based on formulating resting contact as a linear complementarity problem, determines the resting contact forces analytically to prevent interpenetration. The analytical method exhibits expected-case polynomial complexity in the number of contact points, and may fail to find a solution in polynomial time when friction is modeled. We present a fast penalty method that minimizes oscillatory behavior and leads to little penetration during resting contact; our method compares favorably to the analytical method with regard to these two measures, while exhibiting much faster performance both asymptotically and empirically.", "abstracts": [ { "abstractType": "Regular", "content": "Two methods have been used extensively to model resting contact for rigid body simulation. The first approach, the penalty method, applies virtual springs to surfaces in contact to minimize interpenetration. This method, as typically implemented, results in oscillatory behavior and considerable penetration. The second approach, based on formulating resting contact as a linear complementarity problem, determines the resting contact forces analytically to prevent interpenetration. The analytical method exhibits expected-case polynomial complexity in the number of contact points, and may fail to find a solution in polynomial time when friction is modeled. We present a fast penalty method that minimizes oscillatory behavior and leads to little penetration during resting contact; our method compares favorably to the analytical method with regard to these two measures, while exhibiting much faster performance both asymptotically and empirically.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Two methods have been used extensively to model resting contact for rigid body simulation. The first approach, the penalty method, applies virtual springs to surfaces in contact to minimize interpenetration. This method, as typically implemented, results in oscillatory behavior and considerable penetration. The second approach, based on formulating resting contact as a linear complementarity problem, determines the resting contact forces analytically to prevent interpenetration. The analytical method exhibits expected-case polynomial complexity in the number of contact points, and may fail to find a solution in polynomial time when friction is modeled. We present a fast penalty method that minimizes oscillatory behavior and leads to little penetration during resting contact; our method compares favorably to the analytical method with regard to these two measures, while exhibiting much faster performance both asymptotically and empirically.", "title": "A Fast and Stable Penalty Method for Rigid Body Simulation", "normalizedTitle": "A Fast and Stable Penalty Method for Rigid Body Simulation", "fno": "ttg2008010231", "hasPdf": true, "idPrefix": "tg", "keywords": [], "authors": [ { "givenName": "Evan", "surname": "Drumwright", "fullName": "Evan Drumwright", "affiliation": null, "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2008-01-01 00:00:00", "pubType": "trans", "pages": "231-240", "year": "2008", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/ca/2001/7237/0/00982388", "title": "Merging deformable and rigid body mechanics simulation", "doi": null, "abstractUrl": "/proceedings-article/ca/2001/00982388/12OmNqIhFMw", "parentPublication": { "id": "proceedings/ca/2001/7237/0", "title": "Proceedings Computer Animation 2001. 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{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUxASu0Q", "doi": "10.1109/TVCG.2017.2752620", "abstract": "The 2017 Visualization Career Award goes to Charles (Chuck) Hansen in recognition for his contributions to large scale data visualization, including advances in parallel and volume rendering, novel interaction techniques, and techniques for exploiting hardware; for his leadership in the community as an educator, program chair, and editor; and for providing vision for the development and support of the field. The IEEE Visualization & Graphics Technical Committee (VGTC) is pleased to award Charles Hansen the 2017 Visualization Career Award.", "abstracts": [ { "abstractType": "Regular", "content": "The 2017 Visualization Career Award goes to Charles (Chuck) Hansen in recognition for his contributions to large scale data visualization, including advances in parallel and volume rendering, novel interaction techniques, and techniques for exploiting hardware; for his leadership in the community as an educator, program chair, and editor; and for providing vision for the development and support of the field. The IEEE Visualization & Graphics Technical Committee (VGTC) is pleased to award Charles Hansen the 2017 Visualization Career Award.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "The 2017 Visualization Career Award goes to Charles (Chuck) Hansen in recognition for his contributions to large scale data visualization, including advances in parallel and volume rendering, novel interaction techniques, and techniques for exploiting hardware; for his leadership in the community as an educator, program chair, and editor; and for providing vision for the development and support of the field. The IEEE Visualization & Graphics Technical Committee (VGTC) is pleased to award Charles Hansen the 2017 Visualization Career Award.", "title": "The 2017 Visualization Career Award", "normalizedTitle": "The 2017 Visualization Career Award", "fno": "08165941", "hasPdf": true, "idPrefix": "tg", "keywords": [], "authors": [ { "givenName": "Charles", "surname": "Hansen", "fullName": "Charles Hansen", "affiliation": "University of Utah", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": false, "showRecommendedArticles": false, "isOpenAccess": true, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "xxvi-xxvi", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [], "adjacentArticles": { "previous": { "fno": "08165934", "articleId": "13rRUxASuvl", "__typename": "AdjacentArticleType" }, "next": { "fno": "08165929", "articleId": "13rRUxOve9P", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [], "articleVideos": [] }
{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUxOve9P", "doi": "10.1109/TVCG.2017.2752584", "abstract": "The 2017 Visualization Technical Achievement Award goes to Jeffrey Heer in recognition of his work on the design, development, dissemination, and popularization of languages for visualization. The IEEE Visualization & Graphics Technical Committee (VGTC) is pleased to award Jeffrey Heer the 2017 Visualization Technical Achievement Award.", "abstracts": [ { "abstractType": "Regular", "content": "The 2017 Visualization Technical Achievement Award goes to Jeffrey Heer in recognition of his work on the design, development, dissemination, and popularization of languages for visualization. The IEEE Visualization & Graphics Technical Committee (VGTC) is pleased to award Jeffrey Heer the 2017 Visualization Technical Achievement Award.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "The 2017 Visualization Technical Achievement Award goes to Jeffrey Heer in recognition of his work on the design, development, dissemination, and popularization of languages for visualization. The IEEE Visualization & Graphics Technical Committee (VGTC) is pleased to award Jeffrey Heer the 2017 Visualization Technical Achievement Award.", "title": "The 2017 Visualization Technical Achievement Award", "normalizedTitle": "The 2017 Visualization Technical Achievement Award", "fno": "08165929", "hasPdf": true, "idPrefix": "tg", "keywords": [], "authors": [ { "givenName": "Jeffrey", "surname": "Heer", "fullName": "Jeffrey Heer", "affiliation": "University of Washington", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": false, "showRecommendedArticles": false, "isOpenAccess": true, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "xxvii-xxviii", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [], "adjacentArticles": { "previous": { "fno": "08165941", "articleId": "13rRUxASu0Q", "__typename": "AdjacentArticleType" }, "next": { "fno": "08019861", "articleId": "13rRUwbs2gx", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [], "articleVideos": [] }
{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUwbs2gx", "doi": "10.1109/TVCG.2017.2744878", "abstract": "We present a design study of the TensorFlow Graph Visualizer, part of the TensorFlow machine intelligence platform. This tool helps users understand complex machine learning architectures by visualizing their underlying dataflow graphs. The tool works by applying a series of graph transformations that enable standard layout techniques to produce a legible interactive diagram. To declutter the graph, we decouple non-critical nodes from the layout. To provide an overview, we build a clustered graph using the hierarchical structure annotated in the source code. To support exploration of nested structure on demand, we perform edge bundling to enable stable and responsive cluster expansion. Finally, we detect and highlight repeated structures to emphasize a model's modular composition. To demonstrate the utility of the visualizer, we describe example usage scenarios and report user feedback. Overall, users find the visualizer useful for understanding, debugging, and sharing the structures of their models.", "abstracts": [ { "abstractType": "Regular", "content": "We present a design study of the TensorFlow Graph Visualizer, part of the TensorFlow machine intelligence platform. This tool helps users understand complex machine learning architectures by visualizing their underlying dataflow graphs. The tool works by applying a series of graph transformations that enable standard layout techniques to produce a legible interactive diagram. To declutter the graph, we decouple non-critical nodes from the layout. To provide an overview, we build a clustered graph using the hierarchical structure annotated in the source code. To support exploration of nested structure on demand, we perform edge bundling to enable stable and responsive cluster expansion. Finally, we detect and highlight repeated structures to emphasize a model's modular composition. To demonstrate the utility of the visualizer, we describe example usage scenarios and report user feedback. Overall, users find the visualizer useful for understanding, debugging, and sharing the structures of their models.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "We present a design study of the TensorFlow Graph Visualizer, part of the TensorFlow machine intelligence platform. This tool helps users understand complex machine learning architectures by visualizing their underlying dataflow graphs. The tool works by applying a series of graph transformations that enable standard layout techniques to produce a legible interactive diagram. To declutter the graph, we decouple non-critical nodes from the layout. To provide an overview, we build a clustered graph using the hierarchical structure annotated in the source code. To support exploration of nested structure on demand, we perform edge bundling to enable stable and responsive cluster expansion. Finally, we detect and highlight repeated structures to emphasize a model's modular composition. To demonstrate the utility of the visualizer, we describe example usage scenarios and report user feedback. Overall, users find the visualizer useful for understanding, debugging, and sharing the structures of their models.", "title": "Visualizing Dataflow Graphs of Deep Learning Models in TensorFlow", "normalizedTitle": "Visualizing Dataflow Graphs of Deep Learning Models in TensorFlow", "fno": "08019861", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Visualization", "Layout", "Machine Learning", "Computational Modeling", "Tools", "Neural Networks", "Standards", "Neural Network", "Graph Visualization", "Dataflow Graph", "Clustered Graph" ], "authors": [ { "givenName": "Kanit", "surname": "Wongsuphasawat", "fullName": "Kanit Wongsuphasawat", "affiliation": "Paul G. Allen School of Computer Science & EngineeringUniversity of Washington", "__typename": "ArticleAuthorType" }, { "givenName": "Daniel", "surname": "Smilkov", "fullName": "Daniel Smilkov", "affiliation": "Google Research", "__typename": "ArticleAuthorType" }, { "givenName": "James", "surname": "Wexler", "fullName": "James Wexler", "affiliation": "Google Research", "__typename": "ArticleAuthorType" }, { "givenName": "Jimbo", "surname": "Wilson", "fullName": "Jimbo Wilson", "affiliation": "Google Research", "__typename": "ArticleAuthorType" }, { "givenName": "Dandelion", "surname": "Mané", "fullName": "Dandelion Mané", "affiliation": "Google Research", "__typename": "ArticleAuthorType" }, { "givenName": "Doug", "surname": "Fritz", "fullName": "Doug Fritz", "affiliation": "Google Research", "__typename": "ArticleAuthorType" }, { "givenName": "Dilip", "surname": "Krishnan", "fullName": "Dilip Krishnan", "affiliation": "Google Research", "__typename": "ArticleAuthorType" }, { "givenName": "Fernanda B.", "surname": "Viégas", "fullName": "Fernanda B. Viégas", "affiliation": "Google Research", "__typename": "ArticleAuthorType" }, { "givenName": "Martin", "surname": "Wattenberg", "fullName": "Martin Wattenberg", "affiliation": "Google Research", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "1-12", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/icdmw/2015/8493/0/8493a675", "title": "OLAP Visual Analytics on Large Software Call Graphs with Hierarchical ChordMap", "doi": null, "abstractUrl": "/proceedings-article/icdmw/2015/8493a675/12OmNAWpyrN", "parentPublication": { "id": "proceedings/icdmw/2015/8493/0", "title": "2015 IEEE International Conference on Data Mining Workshop (ICDMW)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icoin/2018/2290/0/08343173", "title": "Top-down parsing for Neural Network Exchange Format (NNEF) in TensorFlow-based deep learning computation", "doi": null, "abstractUrl": "/proceedings-article/icoin/2018/08343173/12OmNArKSie", "parentPublication": { "id": "proceedings/icoin/2018/2290/0", "title": "2018 International Conference on Information Networking (ICOIN)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icde/2017/6543/0/6543a215", "title": "Analyzing and Visualizing Scalar Fields on Graphs", "doi": null, "abstractUrl": "/proceedings-article/icde/2017/6543a215/12OmNxvO038", "parentPublication": { "id": "proceedings/icde/2017/6543/0", "title": "2017 IEEE 33rd International Conference on Data Engineering (ICDE)", "__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/2018/12/08249874", "title": "Graph Thumbnails: Identifying and Comparing Multiple Graphs at a Glance", "doi": null, "abstractUrl": "/journal/tg/2018/12/08249874/14H4WOr0FCU", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2019/03/08307265", "title": "Lineage: Visualizing Multivariate Clinical Data in Genealogy Graphs", "doi": null, "abstractUrl": "/journal/tg/2019/03/08307265/17D45Xbl4Qj", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/prdc/2022/8555/0/855500a236", "title": "Examining the Utility of Differentially Private Synthetic Data Generated using Variational Autoencoder with TensorFlow Privacy", "doi": null, "abstractUrl": "/proceedings-article/prdc/2022/855500a236/1KrgUMo24De", "parentPublication": { "id": "proceedings/prdc/2022/8555/0", "title": "2022 IEEE 27th Pacific Rim International Symposium on Dependable Computing (PRDC)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/hpcc-smartcity-dss/2019/2058/0/205800c467", "title": "swFLOW: A Dataflow Deep Learning Framework on Sunway TaihuLight Supercomputer", "doi": null, "abstractUrl": "/proceedings-article/hpcc-smartcity-dss/2019/205800c467/1dPoA7SsGUE", "parentPublication": { "id": "proceedings/hpcc-smartcity-dss/2019/2058/0", "title": "2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/fpl/2019/4884/0/488400a360", "title": "TensorFlow to Cloud FPGAs: Tradeoffs for Accelerating Deep Neural Networks", "doi": null, "abstractUrl": "/proceedings-article/fpl/2019/488400a360/1eLy7tZ4LXG", "parentPublication": { "id": "proceedings/fpl/2019/4884/0", "title": "2019 29th International Conference on Field Programmable Logic and Applications (FPL)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/scc/2021/2400/0/240000a134", "title": "Improving Dependability of Onboard Deep Learning with Resilient TensorFlow", "doi": null, "abstractUrl": "/proceedings-article/scc/2021/240000a134/1xgBiqzThHq", "parentPublication": { "id": "proceedings/scc/2021/2400/0", "title": "2021 IEEE Space Computing Conference (SCC)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "08165929", "articleId": "13rRUxOve9P", "__typename": "AdjacentArticleType" }, "next": { "fno": "08019849", "articleId": "13rRUytF41G", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [ { "id": "17ShDTXnFqY", "name": "ttg201801-08019861s1.zip", "location": "https://www.computer.org/csdl/api/v1/extra/ttg201801-08019861s1.zip", "extension": "zip", "size": "39.8 MB", "__typename": "WebExtraType" } ], "articleVideos": [] }
{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUytF41G", "doi": "10.1109/TVCG.2017.2745181", "abstract": "Analysts in professional team sport regularly perform analysis to gain strategic and tactical insights into player and team behavior. Goals of team sport analysis regularly include identification of weaknesses of opposing teams, or assessing performance and improvement potential of a coached team. Current analysis workflows are typically based on the analysis of team videos. Also, analysts can rely on techniques from Information Visualization, to depict e.g., player or ball trajectories. However, video analysis is typically a time-consuming process, where the analyst needs to memorize and annotate scenes. In contrast, visualization typically relies on an abstract data model, often using abstract visual mappings, and is not directly linked to the observed movement context anymore. We propose a visual analytics system that tightly integrates team sport video recordings with abstract visualization of underlying trajectory data. We apply appropriate computer vision techniques to extract trajectory data from video input. Furthermore, we apply advanced trajectory and movement analysis techniques to derive relevant team sport analytic measures for region, event and player analysis in the case of soccer analysis. Our system seamlessly integrates video and visualization modalities, enabling analysts to draw on the advantages of both analysis forms. Several expert studies conducted with team sport analysts indicate the effectiveness of our integrated approach.", "abstracts": [ { "abstractType": "Regular", "content": "Analysts in professional team sport regularly perform analysis to gain strategic and tactical insights into player and team behavior. Goals of team sport analysis regularly include identification of weaknesses of opposing teams, or assessing performance and improvement potential of a coached team. Current analysis workflows are typically based on the analysis of team videos. Also, analysts can rely on techniques from Information Visualization, to depict e.g., player or ball trajectories. However, video analysis is typically a time-consuming process, where the analyst needs to memorize and annotate scenes. In contrast, visualization typically relies on an abstract data model, often using abstract visual mappings, and is not directly linked to the observed movement context anymore. We propose a visual analytics system that tightly integrates team sport video recordings with abstract visualization of underlying trajectory data. We apply appropriate computer vision techniques to extract trajectory data from video input. Furthermore, we apply advanced trajectory and movement analysis techniques to derive relevant team sport analytic measures for region, event and player analysis in the case of soccer analysis. Our system seamlessly integrates video and visualization modalities, enabling analysts to draw on the advantages of both analysis forms. Several expert studies conducted with team sport analysts indicate the effectiveness of our integrated approach.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Analysts in professional team sport regularly perform analysis to gain strategic and tactical insights into player and team behavior. Goals of team sport analysis regularly include identification of weaknesses of opposing teams, or assessing performance and improvement potential of a coached team. Current analysis workflows are typically based on the analysis of team videos. Also, analysts can rely on techniques from Information Visualization, to depict e.g., player or ball trajectories. However, video analysis is typically a time-consuming process, where the analyst needs to memorize and annotate scenes. In contrast, visualization typically relies on an abstract data model, often using abstract visual mappings, and is not directly linked to the observed movement context anymore. We propose a visual analytics system that tightly integrates team sport video recordings with abstract visualization of underlying trajectory data. We apply appropriate computer vision techniques to extract trajectory data from video input. Furthermore, we apply advanced trajectory and movement analysis techniques to derive relevant team sport analytic measures for region, event and player analysis in the case of soccer analysis. Our system seamlessly integrates video and visualization modalities, enabling analysts to draw on the advantages of both analysis forms. Several expert studies conducted with team sport analysts indicate the effectiveness of our integrated approach.", "title": "Bring It to the Pitch: Combining Video and Movement Data to Enhance Team Sport Analysis", "normalizedTitle": "Bring It to the Pitch: Combining Video and Movement Data to Enhance Team Sport Analysis", "fno": "08019849", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Data Visualization", "Trajectory", "Visualization", "Feature Extraction", "Video Recording", "Image Color Analysis", "Computer Vision", "Visual Analytics", "Sport Analytics", "Immersive Analytics" ], "authors": [ { "givenName": "Manuel", "surname": "Stein", "fullName": "Manuel Stein", "affiliation": "University of Konstanz", "__typename": "ArticleAuthorType" }, { "givenName": "Halldor", "surname": "Janetzko", "fullName": "Halldor Janetzko", "affiliation": "University of Zürich", "__typename": "ArticleAuthorType" }, { "givenName": "Andreas", "surname": "Lamprecht", "fullName": "Andreas Lamprecht", "affiliation": "University of Konstanz", "__typename": "ArticleAuthorType" }, { "givenName": "Thorsten", "surname": "Breitkreutz", "fullName": "Thorsten Breitkreutz", "affiliation": "University of Konstanz", "__typename": "ArticleAuthorType" }, { "givenName": "Philipp", "surname": "Zimmermann", "fullName": "Philipp Zimmermann", "affiliation": "University of Konstanz", "__typename": "ArticleAuthorType" }, { "givenName": "Bastian", "surname": "Goldlücke", "fullName": "Bastian Goldlücke", "affiliation": "University of Konstanz", "__typename": "ArticleAuthorType" }, { "givenName": "Tobias", "surname": "Schreck", "fullName": "Tobias Schreck", "affiliation": "Graz University of Technology", "__typename": "ArticleAuthorType" }, { "givenName": "Gennady", "surname": "Andrienko", "fullName": "Gennady Andrienko", "affiliation": "Fraunhofer IAIS, Germany", "__typename": "ArticleAuthorType" }, { "givenName": "Michael", "surname": "Grossniklaus", "fullName": "Michael Grossniklaus", "affiliation": "University of Konstanz", "__typename": "ArticleAuthorType" }, { "givenName": "Daniel A.", "surname": "Keim", "fullName": "Daniel A. Keim", "affiliation": "University of Konstanz", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "13-22", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/cvpr/2010/6984/0/05540128", "title": "Motion fields to predict play evolution in dynamic sport scenes", "doi": null, "abstractUrl": "/proceedings-article/cvpr/2010/05540128/12OmNANBZtV", "parentPublication": { "id": "proceedings/cvpr/2010/6984/0", "title": "2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iccvw/2015/9711/0/5720a760", "title": "Understanding Sport Activities from Correspondences of Clustered Trajectories", "doi": null, "abstractUrl": "/proceedings-article/iccvw/2015/5720a760/12OmNvIfDPT", "parentPublication": { "id": "proceedings/iccvw/2015/9711/0", "title": "2015 IEEE International Conference on Computer Vision Workshop (ICCVW)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icis/2016/0806/0/07550783", "title": "Video annotation for players' tactics in sport competition", "doi": null, "abstractUrl": "/proceedings-article/icis/2016/07550783/12OmNyGbI92", "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/unesst/2015/9852/0/9852a014", "title": "A Study on the Design of Customized Sport-Team Matching System Based on Mobile Environments", "doi": null, "abstractUrl": "/proceedings-article/unesst/2015/9852a014/12OmNzSyCif", "parentPublication": { "id": "proceedings/unesst/2015/9852/0", "title": "2015 8th International Conference on u- and e- Service, Science and Technology (UNESST)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icme/2013/0015/0/06607536", "title": "Multi-sensor fusion for sport genre classification of user generated mobile videos", "doi": null, "abstractUrl": "/proceedings-article/icme/2013/06607536/12OmNzvhvBH", "parentPublication": { "id": "proceedings/icme/2013/0015/0", "title": "2013 IEEE International Conference on Multimedia and Expo (ICME)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/bdva/2018/9194/0/08534022", "title": "Revealing the Invisible: Visual Analytics and Explanatory Storytelling for Advanced Team Sport Analysis", "doi": null, "abstractUrl": "/proceedings-article/bdva/2018/08534022/17D45WODasQ", "parentPublication": { "id": "proceedings/bdva/2018/9194/0", "title": "2018 International Symposium on Big Data Visual and Immersive Analytics (BDVA)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/cvprw/2022/8739/0/873900d460", "title": "Efficient tracking of team sport players with few game-specific annotations", "doi": null, "abstractUrl": "/proceedings-article/cvprw/2022/873900d460/1G56wfpxHI4", "parentPublication": { "id": "proceedings/cvprw/2022/8739/0", "title": "2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/cvprw/2019/2506/0/250600c477", "title": "Associative Embedding for Team Discrimination", "doi": null, "abstractUrl": "/proceedings-article/cvprw/2019/250600c477/1iTvpUmBbk4", "parentPublication": { "id": "proceedings/cvprw/2019/2506/0", "title": "2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)", "__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": "proceedings/smartcomp/2020/6997/0/699700a148", "title": "A Wireless System for Sport Assessment", "doi": null, "abstractUrl": "/proceedings-article/smartcomp/2020/699700a148/1oxobKMor9C", "parentPublication": { "id": "proceedings/smartcomp/2020/6997/0", "title": "2020 IEEE International Conference on Smart Computing (SMARTCOMP)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "08019861", "articleId": "13rRUwbs2gx", "__typename": "AdjacentArticleType" }, "next": { "fno": "08022952", "articleId": "13rRUyogGAi", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [], "articleVideos": [] }
{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUyogGAi", "doi": "10.1109/TVCG.2017.2744419", "abstract": "The increasing availability of spatiotemporal data continuously collected from various sources provides new opportunities for a timely understanding of the data in their spatial and temporal context. Finding abnormal patterns in such data poses significant challenges. Given that there is often no clear boundary between normal and abnormal patterns, existing solutions are limited in their capacity of identifying anomalies in large, dynamic and heterogeneous data, interpreting anomalies in their multifaceted, spatiotemporal context, and allowing users to provide feedback in the analysis loop. In this work, we introduce a unified visual interactive system and framework, Voila, for interactively detecting anomalies in spatiotemporal data collected from a streaming data source. The system is designed to meet two requirements in real-world applications, i.e., online monitoring and interactivity. We propose a novel tensor-based anomaly analysis algorithm with visualization and interaction design that dynamically produces contextualized, interpretable data summaries and allows for interactively ranking anomalous patterns based on user input. Using the “smart city” as an example scenario, we demonstrate the effectiveness of the proposed framework through quantitative evaluation and qualitative case studies.", "abstracts": [ { "abstractType": "Regular", "content": "The increasing availability of spatiotemporal data continuously collected from various sources provides new opportunities for a timely understanding of the data in their spatial and temporal context. Finding abnormal patterns in such data poses significant challenges. Given that there is often no clear boundary between normal and abnormal patterns, existing solutions are limited in their capacity of identifying anomalies in large, dynamic and heterogeneous data, interpreting anomalies in their multifaceted, spatiotemporal context, and allowing users to provide feedback in the analysis loop. In this work, we introduce a unified visual interactive system and framework, Voila, for interactively detecting anomalies in spatiotemporal data collected from a streaming data source. The system is designed to meet two requirements in real-world applications, i.e., online monitoring and interactivity. We propose a novel tensor-based anomaly analysis algorithm with visualization and interaction design that dynamically produces contextualized, interpretable data summaries and allows for interactively ranking anomalous patterns based on user input. Using the “smart city” as an example scenario, we demonstrate the effectiveness of the proposed framework through quantitative evaluation and qualitative case studies.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "The increasing availability of spatiotemporal data continuously collected from various sources provides new opportunities for a timely understanding of the data in their spatial and temporal context. Finding abnormal patterns in such data poses significant challenges. Given that there is often no clear boundary between normal and abnormal patterns, existing solutions are limited in their capacity of identifying anomalies in large, dynamic and heterogeneous data, interpreting anomalies in their multifaceted, spatiotemporal context, and allowing users to provide feedback in the analysis loop. In this work, we introduce a unified visual interactive system and framework, Voila, for interactively detecting anomalies in spatiotemporal data collected from a streaming data source. The system is designed to meet two requirements in real-world applications, i.e., online monitoring and interactivity. We propose a novel tensor-based anomaly analysis algorithm with visualization and interaction design that dynamically produces contextualized, interpretable data summaries and allows for interactively ranking anomalous patterns based on user input. Using the “smart city” as an example scenario, we demonstrate the effectiveness of the proposed framework through quantitative evaluation and qualitative case studies.", "title": "Voila: Visual Anomaly Detection and Monitoring with Streaming Spatiotemporal Data", "normalizedTitle": "Voila: Visual Anomaly Detection and Monitoring with Streaming Spatiotemporal Data", "fno": "08022952", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Spatiotemporal Phenomena", "Data Visualization", "Anomaly Detection", "Visualization", "Tensile Stress", "Algorithm Design And Analysis", "Data Models", "Anomaly Detection", "Visual Analysis" ], "authors": [ { "givenName": "Nan", "surname": "Cao", "fullName": "Nan Cao", "affiliation": "Intelligent Big Data Visualization (iDVx) LabTongji University", "__typename": "ArticleAuthorType" }, { "givenName": "Chaoguang", "surname": "Lin", "fullName": "Chaoguang Lin", "affiliation": "Intelligent Big Data Visualization (iDVx) LabTongji University", "__typename": "ArticleAuthorType" }, { "givenName": "Qiuhan", "surname": "Zhu", "fullName": "Qiuhan Zhu", "affiliation": "Intelligent Big Data Visualization (iDVx) LabTongji University", "__typename": "ArticleAuthorType" }, { "givenName": "Yu-Ru", "surname": "Lin", "fullName": "Yu-Ru Lin", "affiliation": "University of Pittsburgh", "__typename": "ArticleAuthorType" }, { "givenName": "Xian", "surname": "Teng", "fullName": "Xian Teng", "affiliation": "University of Pittsburgh", "__typename": "ArticleAuthorType" }, { "givenName": "Xidao", "surname": "Wen", "fullName": "Xidao Wen", "affiliation": "University of Pittsburgh", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "23-33", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/vast/2014/6227/0/07042482", "title": "An insight- and task-based methodology for evaluating spatiotemporal visual analytics", "doi": null, "abstractUrl": "/proceedings-article/vast/2014/07042482/12OmNwp74wP", "parentPublication": { "id": "proceedings/vast/2014/6227/0", "title": "2014 IEEE Conference on Visual Analytics Science and Technology (VAST)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2018/03/07847429", "title": "Data Flow Analysis and Visualization for Spatiotemporal Statistical Data without Trajectory Information", "doi": null, "abstractUrl": "/journal/tg/2018/03/07847429/13rRUygBw7h", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vast/2017/3163/0/08585564", "title": "Interactive Visual Analytics Application for Spatiotemporal Movement Data VAST Challenge 2017 Mini-Challenge 1: Award for Actionable and Detailed Analysis", "doi": null, "abstractUrl": "/proceedings-article/vast/2017/08585564/17D45VsBU7R", "parentPublication": { "id": "proceedings/vast/2017/3163/0", "title": "2017 IEEE Conference on Visual Analytics Science and Technology (VAST)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2019/01/08440040", "title": "A Visual Analytics Framework for Spatiotemporal Trade Network Analysis", "doi": null, "abstractUrl": "/journal/tg/2019/01/08440040/17D45WHONjL", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tk/5555/01/09793649", "title": "A2DJP: A Two Graph-based Component Fused Learning Framework for Urban Anomaly Distribution and Duration Joint-Prediction", "doi": null, "abstractUrl": "/journal/tk/5555/01/09793649/1E5LzxMmqK4", "parentPublication": { "id": "trans/tk", "title": "IEEE Transactions on Knowledge & Data Engineering", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/hpcc-dss-smartcity-dependsys/2022/1993/0/199300a847", "title": "Fine-grained Spatiotemporal Features-Based for Anomaly Detection in Microservice Systems", "doi": null, "abstractUrl": "/proceedings-article/hpcc-dss-smartcity-dependsys/2022/199300a847/1LSPIYjvEOc", "parentPublication": { "id": "proceedings/hpcc-dss-smartcity-dependsys/2022/1993/0", "title": "2022 IEEE 24th Int Conf on High Performance Computing & Communications; 8th Int Conf on Data Science & Systems; 20th Int Conf on Smart City; 8th Int Conf on Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/big-data/2019/0858/0/09005687", "title": "Visual Anomaly Detection in Event Sequence Data", "doi": null, "abstractUrl": "/proceedings-article/big-data/2019/09005687/1hJs7AGCWuA", "parentPublication": { "id": "proceedings/big-data/2019/0858/0", "title": "2019 IEEE International Conference on Big Data (Big Data)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icci*cc/2019/1419/0/09146048", "title": "Sparse spatiotemporal feature learning for pipeline anomaly detection", "doi": null, "abstractUrl": "/proceedings-article/icci*cc/2019/09146048/1lFJf6353ig", "parentPublication": { "id": "proceedings/icci*cc/2019/1419/0", "title": "2019 IEEE 18th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)", "__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" }, { "id": "trans/tg/2022/01/09552191", "title": "DDLVis: Real-time Visual Query of Spatiotemporal Data Distribution via Density Dictionary Learning", "doi": null, "abstractUrl": "/journal/tg/2022/01/09552191/1xic2jmfPOg", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "08019849", "articleId": "13rRUytF41G", "__typename": "AdjacentArticleType" }, "next": { "fno": "08017616", "articleId": "13rRUyY294H", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [ { "id": "17ShDTYesXb", "name": "ttg201801-08022952s1.zip", "location": "https://www.computer.org/csdl/api/v1/extra/ttg201801-08022952s1.zip", "extension": "zip", "size": "50 MB", "__typename": "WebExtraType" } ], "articleVideos": [] }
{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUyY294H", "doi": "10.1109/TVCG.2017.2744322", "abstract": "Clustering of trajectories of moving objects by similarity is an important technique in movement analysis. Existing distance functions assess the similarity between trajectories based on properties of the trajectory points or segments. The properties may include the spatial positions, times, and thematic attributes. There may be a need to focus the analysis on certain parts of trajectories, i.e., points and segments that have particular properties. According to the analysis focus, the analyst may need to cluster trajectories by similarity of their relevant parts only. Throughout the analysis process, the focus may change, and different parts of trajectories may become relevant. We propose an analytical workflow in which interactive filtering tools are used to attach relevance flags to elements of trajectories, clustering is done using a distance function that ignores irrelevant elements, and the resulting clusters are summarized for further analysis. We demonstrate how this workflow can be useful for different analysis tasks in three case studies with real data from the domain of air traffic. We propose a suite of generic techniques and visualization guidelines to support movement data analysis by means of relevance-aware trajectory clustering.", "abstracts": [ { "abstractType": "Regular", "content": "Clustering of trajectories of moving objects by similarity is an important technique in movement analysis. Existing distance functions assess the similarity between trajectories based on properties of the trajectory points or segments. The properties may include the spatial positions, times, and thematic attributes. There may be a need to focus the analysis on certain parts of trajectories, i.e., points and segments that have particular properties. According to the analysis focus, the analyst may need to cluster trajectories by similarity of their relevant parts only. Throughout the analysis process, the focus may change, and different parts of trajectories may become relevant. We propose an analytical workflow in which interactive filtering tools are used to attach relevance flags to elements of trajectories, clustering is done using a distance function that ignores irrelevant elements, and the resulting clusters are summarized for further analysis. We demonstrate how this workflow can be useful for different analysis tasks in three case studies with real data from the domain of air traffic. We propose a suite of generic techniques and visualization guidelines to support movement data analysis by means of relevance-aware trajectory clustering.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Clustering of trajectories of moving objects by similarity is an important technique in movement analysis. Existing distance functions assess the similarity between trajectories based on properties of the trajectory points or segments. The properties may include the spatial positions, times, and thematic attributes. There may be a need to focus the analysis on certain parts of trajectories, i.e., points and segments that have particular properties. According to the analysis focus, the analyst may need to cluster trajectories by similarity of their relevant parts only. Throughout the analysis process, the focus may change, and different parts of trajectories may become relevant. We propose an analytical workflow in which interactive filtering tools are used to attach relevance flags to elements of trajectories, clustering is done using a distance function that ignores irrelevant elements, and the resulting clusters are summarized for further analysis. We demonstrate how this workflow can be useful for different analysis tasks in three case studies with real data from the domain of air traffic. We propose a suite of generic techniques and visualization guidelines to support movement data analysis by means of relevance-aware trajectory clustering.", "title": "Clustering Trajectories by Relevant Parts for Air Traffic Analysis", "normalizedTitle": "Clustering Trajectories by Relevant Parts for Air Traffic Analysis", "fno": "08017616", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Trajectory", "Data Visualization", "Three Dimensional Displays", "Guidelines", "Visualization", "Clustering Algorithms", "Algorithm Design And Analysis", "Visual Analytics", "Movement Data Analysis", "Trajectory Clustering", "Air Traffic" ], "authors": [ { "givenName": "Gennady", "surname": "Andrienko", "fullName": "Gennady Andrienko", "affiliation": "Fraunhofer IAIS, City University, London", "__typename": "ArticleAuthorType" }, { "givenName": "Natalia", "surname": "Andrienko", "fullName": "Natalia Andrienko", "affiliation": "Fraunhofer IAIS, City University, London", "__typename": "ArticleAuthorType" }, { "givenName": "Georg", "surname": "Fuchs", "fullName": "Georg Fuchs", "affiliation": "Fraunhofer Institute IAIS", "__typename": "ArticleAuthorType" }, { "givenName": "Jose Manuel Cordero", "surname": "Garcia", "fullName": "Jose Manuel Cordero Garcia", "affiliation": "CRIDA (Reference Center for Research, Development and Innovation in ATM)", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "34-44", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/cw/2014/4677/0/4677a174", "title": "Real-Time Animated Visualization of Massive Air-Traffic Trajectories", "doi": null, "abstractUrl": "/proceedings-article/cw/2014/4677a174/12OmNwF0BTG", "parentPublication": { "id": "proceedings/cw/2014/4677/0", "title": "2014 International Conference on Cyberworlds (CW)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icdmw/2010/4257/0/4257a209", "title": "Comparing Vessel Trajectories Using Geographical Domain Knowledge and Alignments", "doi": null, "abstractUrl": "/proceedings-article/icdmw/2010/4257a209/12OmNyOq4Rr", "parentPublication": { "id": "proceedings/icdmw/2010/4257/0", "title": "2010 IEEE International Conference on Data Mining Workshops", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icpr/2012/2216/0/06460699", "title": "Video object segmentation by clustering region trajectories", "doi": null, "abstractUrl": "/proceedings-article/icpr/2012/06460699/12OmNyRPgBQ", "parentPublication": { "id": "proceedings/icpr/2012/2216/0", "title": "2012 21st International Conference on Pattern Recognition (ICPR 2012)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/pacificvis/2015/6879/0/07156362", "title": "Analyzing delays in trajectories", "doi": null, "abstractUrl": "/proceedings-article/pacificvis/2015/07156362/12OmNylsZUZ", "parentPublication": { "id": "proceedings/pacificvis/2015/6879/0", "title": "2015 IEEE Pacific Visualization Symposium (PacificVis)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/fskd/2008/3305/4/3305d256", "title": "Mining Traffic Condition from Trajectories", "doi": null, "abstractUrl": "/proceedings-article/fskd/2008/3305d256/12OmNz6iOaH", "parentPublication": { "id": "proceedings/fskd/2008/3305/4", "title": "Fuzzy Systems and Knowledge Discovery, Fourth International Conference on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2015/01/06851202", "title": "SimpliFly: A Methodology for Simplification and Thematic Enhancement of Trajectories", "doi": null, "abstractUrl": "/journal/tg/2015/01/06851202/13rRUEgarnL", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/big-data/2017/2715/0/08258021", "title": "Event-based non-parametric clustering of team sport trajectories", "doi": null, "abstractUrl": "/proceedings-article/big-data/2017/08258021/17D45Vu1TxM", "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/2019/01/08456856", "title": "Visualization of Large Molecular Trajectories", "doi": null, "abstractUrl": "/journal/tg/2019/01/08456856/17D45Xbl4Qi", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, 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{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUyft7D8", "doi": "10.1109/TVCG.2017.2745083", "abstract": "Event sequences analysis plays an important role in many application domains such as customer behavior analysis, electronic health record analysis and vehicle fault diagnosis. Real-world event sequence data is often noisy and complex with high event cardinality, making it a challenging task to construct concise yet comprehensive overviews for such data. In this paper, we propose a novel visualization technique based on the minimum description length (MDL) principle to construct a coarse-level overview of event sequence data while balancing the information loss in it. The method addresses a fundamental trade-off in visualization design: reducing visual clutter vs. increasing the information content in a visualization. The method enables simultaneous sequence clustering and pattern extraction and is highly tolerant to noises such as missing or additional events in the data. Based on this approach we propose a visual analytics framework with multiple levels-of-detail to facilitate interactive data exploration. We demonstrate the usability and effectiveness of our approach through case studies with two real-world datasets. One dataset showcases a new application domain for event sequence visualization, i.e., fault development path analysis in vehicles for predictive maintenance. We also discuss the strengths and limitations of the proposed method based on user feedback.", "abstracts": [ { "abstractType": "Regular", "content": "Event sequences analysis plays an important role in many application domains such as customer behavior analysis, electronic health record analysis and vehicle fault diagnosis. Real-world event sequence data is often noisy and complex with high event cardinality, making it a challenging task to construct concise yet comprehensive overviews for such data. In this paper, we propose a novel visualization technique based on the minimum description length (MDL) principle to construct a coarse-level overview of event sequence data while balancing the information loss in it. The method addresses a fundamental trade-off in visualization design: reducing visual clutter vs. increasing the information content in a visualization. The method enables simultaneous sequence clustering and pattern extraction and is highly tolerant to noises such as missing or additional events in the data. Based on this approach we propose a visual analytics framework with multiple levels-of-detail to facilitate interactive data exploration. We demonstrate the usability and effectiveness of our approach through case studies with two real-world datasets. One dataset showcases a new application domain for event sequence visualization, i.e., fault development path analysis in vehicles for predictive maintenance. We also discuss the strengths and limitations of the proposed method based on user feedback.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Event sequences analysis plays an important role in many application domains such as customer behavior analysis, electronic health record analysis and vehicle fault diagnosis. Real-world event sequence data is often noisy and complex with high event cardinality, making it a challenging task to construct concise yet comprehensive overviews for such data. In this paper, we propose a novel visualization technique based on the minimum description length (MDL) principle to construct a coarse-level overview of event sequence data while balancing the information loss in it. The method addresses a fundamental trade-off in visualization design: reducing visual clutter vs. increasing the information content in a visualization. The method enables simultaneous sequence clustering and pattern extraction and is highly tolerant to noises such as missing or additional events in the data. Based on this approach we propose a visual analytics framework with multiple levels-of-detail to facilitate interactive data exploration. We demonstrate the usability and effectiveness of our approach through case studies with two real-world datasets. One dataset showcases a new application domain for event sequence visualization, i.e., fault development path analysis in vehicles for predictive maintenance. We also discuss the strengths and limitations of the proposed method based on user feedback.", "title": "Sequence Synopsis: Optimize Visual Summary of Temporal Event Data", "normalizedTitle": "Sequence Synopsis: Optimize Visual Summary of Temporal Event Data", "fno": "08025640", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Data Visualization", "Data Mining", "Algorithm Design And Analysis", "Data Models", "Visual Analytics", "Noise Measurement", "Time Series Data", "Data Transformation And Representation", "Visual Knowledge Representation", "Visual Analytics" ], "authors": [ { "givenName": "Yuanzhe", "surname": "Chen", "fullName": "Yuanzhe Chen", "affiliation": "Hong Kong University of Science and Technology", "__typename": "ArticleAuthorType" }, { "givenName": "Panpan", "surname": "Xu", "fullName": "Panpan Xu", "affiliation": "Bosch Research North America, Palo Alto, CA", "__typename": "ArticleAuthorType" }, { "givenName": "Liu", "surname": "Ren", "fullName": "Liu Ren", "affiliation": "Bosch Research North America, Palo Alto, CA", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "45-55", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/bigcomp/2018/3649/0/364901a009", "title": "Visual Analysis of Spatio-Temporal Distribution and Retweet Relation in Weibo Event", "doi": null, "abstractUrl": "/proceedings-article/bigcomp/2018/364901a009/12OmNxFaLCs", "parentPublication": { "id": "proceedings/bigcomp/2018/3649/0", "title": "2018 IEEE International Conference on Big Data and Smart Computing (BigComp)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2016/12/07368928", "title": "What May Visualization Processes Optimize?", "doi": null, "abstractUrl": "/journal/tg/2016/12/07368928/13rRUILLkDV", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2019/01/08440811", "title": "Visual Progression Analysis of Event Sequence Data", "doi": null, "abstractUrl": "/journal/tg/2019/01/08440811/17D45WXIkG6", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2020/01/08807220", "title": "Visual Analysis of High-Dimensional Event Sequence Data via Dynamic Hierarchical Aggregation", "doi": null, "abstractUrl": "/journal/tg/2020/01/08807220/1cG6bfa8KkM", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vis/2019/4941/0/08933770", "title": "Analyzing Time Attributes in Temporal Event Sequences", "doi": null, "abstractUrl": "/proceedings-article/vis/2019/08933770/1fTgG41zCqA", "parentPublication": { "id": "proceedings/vis/2019/4941/0", "title": "2019 IEEE Visualization Conference (VIS)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2021/02/09222294", "title": "Visual Causality Analysis of Event Sequence Data", "doi": null, "abstractUrl": "/journal/tg/2021/02/09222294/1nTqOCPOdTq", "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/2022/08/09316994", "title": "Visual Drift Detection for Event Sequence Data of Business Processes", "doi": null, "abstractUrl": "/journal/tg/2022/08/09316994/1qdT8aC5c1q", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2022/12/09497654", "title": "Survey on Visual Analysis of Event Sequence Data", "doi": null, "abstractUrl": "/journal/tg/2022/12/09497654/1vzYfkJCG64", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2022/01/09557226", "title": "Sequen-C: A Multilevel Overview of Temporal Event Sequences", "doi": null, "abstractUrl": "/journal/tg/2022/01/09557226/1xlw03gAaKQ", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "08017616", "articleId": "13rRUyY294H", "__typename": "AdjacentArticleType" }, "next": { "fno": "08017612", "articleId": "13rRUwkxc5r", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [ { "id": "17ShDTXWRJs", "name": "ttg201801-08025640s1.zip", "location": "https://www.computer.org/csdl/api/v1/extra/ttg201801-08025640s1.zip", "extension": "zip", "size": "77.5 MB", "__typename": "WebExtraType" } ], "articleVideos": [] }
{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUwkxc5r", "doi": "10.1109/TVCG.2017.2745320", "abstract": "Event sequence data such as electronic health records, a person's academic records, or car service records, are ordered series of events which have occurred over a period of time. Analyzing collections of event sequences can reveal common or semantically important sequential patterns. For example, event sequence analysis might reveal frequently used care plans for treating a disease, typical publishing patterns of professors, and the patterns of service that result in a well-maintained car. It is challenging, however, to visually explore large numbers of event sequences, or sequences with large numbers of event types. Existing methods focus on extracting explicitly matching patterns of events using statistical analysis to create stages of event progression over time. However, these methods fail to capture latent clusters of similar but not identical evolutions of event sequences. In this paper, we introduce a novel visualization system named EventThread which clusters event sequences into threads based on tensor analysis and visualizes the latent stage categories and evolution patterns by interactively grouping the threads by similarity into time-specific clusters. We demonstrate the effectiveness of EventThread through usage scenarios in three different application domains and via interviews with an expert user.", "abstracts": [ { "abstractType": "Regular", "content": "Event sequence data such as electronic health records, a person's academic records, or car service records, are ordered series of events which have occurred over a period of time. Analyzing collections of event sequences can reveal common or semantically important sequential patterns. For example, event sequence analysis might reveal frequently used care plans for treating a disease, typical publishing patterns of professors, and the patterns of service that result in a well-maintained car. It is challenging, however, to visually explore large numbers of event sequences, or sequences with large numbers of event types. Existing methods focus on extracting explicitly matching patterns of events using statistical analysis to create stages of event progression over time. However, these methods fail to capture latent clusters of similar but not identical evolutions of event sequences. In this paper, we introduce a novel visualization system named EventThread which clusters event sequences into threads based on tensor analysis and visualizes the latent stage categories and evolution patterns by interactively grouping the threads by similarity into time-specific clusters. We demonstrate the effectiveness of EventThread through usage scenarios in three different application domains and via interviews with an expert user.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Event sequence data such as electronic health records, a person's academic records, or car service records, are ordered series of events which have occurred over a period of time. Analyzing collections of event sequences can reveal common or semantically important sequential patterns. For example, event sequence analysis might reveal frequently used care plans for treating a disease, typical publishing patterns of professors, and the patterns of service that result in a well-maintained car. It is challenging, however, to visually explore large numbers of event sequences, or sequences with large numbers of event types. Existing methods focus on extracting explicitly matching patterns of events using statistical analysis to create stages of event progression over time. However, these methods fail to capture latent clusters of similar but not identical evolutions of event sequences. In this paper, we introduce a novel visualization system named EventThread which clusters event sequences into threads based on tensor analysis and visualizes the latent stage categories and evolution patterns by interactively grouping the threads by similarity into time-specific clusters. We demonstrate the effectiveness of EventThread through usage scenarios in three different application domains and via interviews with an expert user.", "title": "EventThread: Visual Summarization and Stage Analysis of Event Sequence Data", "normalizedTitle": "EventThread: Visual Summarization and Stage Analysis of Event Sequence Data", "fno": "08017612", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Data Visualization", "Visualization", "Automobiles", "Hidden Markov Models", "Algorithm Design And Analysis", "Semantics", "Clustering Algorithms", "Visual Knowledge Representation", "Visual Knowledge Discovery", "Data Clustering", "Time Series Data", "Illustrative Visualization" ], "authors": [ { "givenName": "Shunan", "surname": "Guo", "fullName": "Shunan Guo", "affiliation": "East China Normal University", "__typename": "ArticleAuthorType" }, { "givenName": "Ke", "surname": "Xu", "fullName": "Ke Xu", "affiliation": "Hong Kong University of Science and Technology", "__typename": "ArticleAuthorType" }, { "givenName": "Rongwen", "surname": "Zhao", "fullName": "Rongwen Zhao", "affiliation": "iDVx LabTongji University", "__typename": "ArticleAuthorType" }, { "givenName": "David", "surname": "Gotz", "fullName": "David Gotz", "affiliation": "University of North Carolina, Chapel Hill", "__typename": "ArticleAuthorType" }, { "givenName": "Hongyuan", "surname": "Zha", "fullName": "Hongyuan Zha", "affiliation": "East China Normal University", "__typename": "ArticleAuthorType" }, { "givenName": "Nan", "surname": "Cao", "fullName": "Nan Cao", "affiliation": "iDVx LabTongji University", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "56-65", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/vast/2016/5661/0/07883512", "title": "EventAction: Visual analytics for temporal event sequence recommendation", "doi": null, "abstractUrl": "/proceedings-article/vast/2016/07883512/12OmNBDQbnR", "parentPublication": { "id": "proceedings/vast/2016/5661/0", "title": "2016 IEEE Conference on Visual Analytics Science and Technology (VAST)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vast/2012/4752/0/06400494", "title": "Visual cluster exploration of web clickstream data", "doi": null, "abstractUrl": "/proceedings-article/vast/2012/06400494/12OmNxHJ9t7", "parentPublication": { "id": "proceedings/vast/2012/4752/0", "title": "2012 IEEE Conference on Visual Analytics Science and Technology (VAST 2012)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vast/2014/6227/0/07042504", "title": "Visual process mining: Event data exploration and analysis", "doi": null, "abstractUrl": "/proceedings-article/vast/2014/07042504/12OmNzcPAxM", "parentPublication": { "id": "proceedings/vast/2014/6227/0", "title": "2014 IEEE Conference on Visual Analytics Science and Technology (VAST)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2013/12/ttg2013122227", "title": "Temporal Event Sequence Simplification", "doi": null, "abstractUrl": "/journal/tg/2013/12/ttg2013122227/13rRUwjXZSd", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vds/2017/3185/0/08573439", "title": "Clear Visual Separation of Temporal Event Sequences", "doi": null, "abstractUrl": "/proceedings-article/vds/2017/08573439/17D45W9KVGv", "parentPublication": { "id": "proceedings/vds/2017/3185/0", "title": "2017 IEEE Visualization in Data Science (VDS)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2019/01/08440811", "title": "Visual Progression Analysis of Event Sequence Data", "doi": null, "abstractUrl": "/journal/tg/2019/01/08440811/17D45WXIkG6", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vis/2019/4941/0/08933770", "title": "Analyzing Time Attributes in Temporal Event Sequences", "doi": null, "abstractUrl": "/proceedings-article/vis/2019/08933770/1fTgG41zCqA", "parentPublication": { "id": "proceedings/vis/2019/4941/0", "title": "2019 IEEE Visualization Conference (VIS)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2021/02/09222294", "title": "Visual Causality Analysis of Event Sequence Data", "doi": null, "abstractUrl": "/journal/tg/2021/02/09222294/1nTqOCPOdTq", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "mags/ex/2021/03/09272840", "title": "Anomalous Event Sequence Detection", "doi": null, "abstractUrl": "/magazine/ex/2021/03/09272840/1p6aQYYP55e", "parentPublication": { "id": "mags/ex", "title": "IEEE Intelligent Systems", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2022/12/09497654", "title": "Survey on Visual Analysis of Event Sequence Data", "doi": null, "abstractUrl": "/journal/tg/2022/12/09497654/1vzYfkJCG64", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "08025640", "articleId": "13rRUyft7D8", "__typename": "AdjacentArticleType" }, "next": { "fno": "08022969", "articleId": "13rRUygBw7g", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [ { "id": "17ShDTXnFv2", "name": "ttg201801-08017612s1.zip", "location": "https://www.computer.org/csdl/api/v1/extra/ttg201801-08017612s1.zip", "extension": "zip", "size": "55.5 MB", "__typename": "WebExtraType" } ], "articleVideos": [] }
{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUygBw7g", "doi": "10.1109/TVCG.2017.2744686", "abstract": "This design study focuses on the analysis of a time sequence of categorical sequences. Such data is relevant for the geoscientific research field of landscape and climate development. It results from microscopic analysis of lake sediment cores. The goal is to gain hypotheses about landscape evolution and climate conditions in the past. To this end, geoscientists identify which categorical sequences are similar in the sense that they indicate similar conditions. Categorical sequences are similar if they have similar meaning (semantic similarity) and appear in similar time periods (temporal similarity). For data sets with many different categorical sequences, the task to identify similar sequences becomes a challenge. Our contribution is a tailored visual analysis concept that effectively supports the analytical process. Our visual interface comprises coupled visualizations of semantics and temporal context for the exploration and assessment of the similarity of categorical sequences. Integrated automatic methods reduce the analytical effort substantially. They (1) extract unique sequences in the data and (2) rank sequences by a similarity measure during the search for similar sequences. We evaluated our concept by demonstrations of our prototype to a larger audience and hands-on analysis sessions for two different lakes. According to geoscientists, our approach fills an important methodological gap in the application domain.", "abstracts": [ { "abstractType": "Regular", "content": "This design study focuses on the analysis of a time sequence of categorical sequences. Such data is relevant for the geoscientific research field of landscape and climate development. It results from microscopic analysis of lake sediment cores. The goal is to gain hypotheses about landscape evolution and climate conditions in the past. To this end, geoscientists identify which categorical sequences are similar in the sense that they indicate similar conditions. Categorical sequences are similar if they have similar meaning (semantic similarity) and appear in similar time periods (temporal similarity). For data sets with many different categorical sequences, the task to identify similar sequences becomes a challenge. Our contribution is a tailored visual analysis concept that effectively supports the analytical process. Our visual interface comprises coupled visualizations of semantics and temporal context for the exploration and assessment of the similarity of categorical sequences. Integrated automatic methods reduce the analytical effort substantially. They (1) extract unique sequences in the data and (2) rank sequences by a similarity measure during the search for similar sequences. We evaluated our concept by demonstrations of our prototype to a larger audience and hands-on analysis sessions for two different lakes. According to geoscientists, our approach fills an important methodological gap in the application domain.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "This design study focuses on the analysis of a time sequence of categorical sequences. Such data is relevant for the geoscientific research field of landscape and climate development. It results from microscopic analysis of lake sediment cores. The goal is to gain hypotheses about landscape evolution and climate conditions in the past. To this end, geoscientists identify which categorical sequences are similar in the sense that they indicate similar conditions. Categorical sequences are similar if they have similar meaning (semantic similarity) and appear in similar time periods (temporal similarity). For data sets with many different categorical sequences, the task to identify similar sequences becomes a challenge. Our contribution is a tailored visual analysis concept that effectively supports the analytical process. Our visual interface comprises coupled visualizations of semantics and temporal context for the exploration and assessment of the similarity of categorical sequences. Integrated automatic methods reduce the analytical effort substantially. They (1) extract unique sequences in the data and (2) rank sequences by a similarity measure during the search for similar sequences. We evaluated our concept by demonstrations of our prototype to a larger audience and hands-on analysis sessions for two different lakes. According to geoscientists, our approach fills an important methodological gap in the application domain.", "title": "Understanding a Sequence of Sequences: Visual Exploration of Categorical States in Lake Sediment Cores", "normalizedTitle": "Understanding a Sequence of Sequences: Visual Exploration of Categorical States in Lake Sediment Cores", "fno": "08022969", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Meteorology", "Semantics", "Sediments", "Visualization", "Lakes", "Microscopy", "Prototypes", "Visualization In Earth Science", "Time Series Data", "Categorical Data", "Design Study" ], "authors": [ { "givenName": "Andrea", "surname": "Unger", "fullName": "Andrea Unger", "affiliation": "GFZ German Research Centre for Geosciences", "__typename": "ArticleAuthorType" }, { "givenName": "Nadine", "surname": "Dräger", "fullName": "Nadine Dräger", "affiliation": "GFZ German Research Centre for Geosciences", "__typename": "ArticleAuthorType" }, { "givenName": "Mike", "surname": "Sips", "fullName": "Mike Sips", "affiliation": "GFZ German Research Centre for Geosciences", "__typename": "ArticleAuthorType" }, { "givenName": "Dirk J.", "surname": "Lehmann", "fullName": "Dirk J. Lehmann", "affiliation": "University of Magdeburg", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "66-76", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/iv/2014/4103/0/4103a084", "title": "A Heatmap-Based Time-Varying Multi-variate Data Visualization Unifying Numeric and Categorical Variables", "doi": null, "abstractUrl": "/proceedings-article/iv/2014/4103a084/12OmNqESuhq", "parentPublication": { "id": "proceedings/iv/2014/4103/0", "title": "2014 18th International Conference on Information Visualisation (IV)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iccea/2010/3982/2/3982b365", "title": "A Hierarchical Clustering Algorithm for Categorical Attributes", "doi": null, "abstractUrl": "/proceedings-article/iccea/2010/3982b365/12OmNvzJG2A", "parentPublication": { "id": "proceedings/iccea/2010/3982/2", "title": "Computer Engineering and Applications, International Conference on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icdm/2011/4408/0/4408a854", "title": "A New Markov Model for Clustering Categorical Sequences", "doi": null, "abstractUrl": "/proceedings-article/icdm/2011/4408a854/12OmNxFJXPI", "parentPublication": { "id": "proceedings/icdm/2011/4408/0", "title": "2011 IEEE 11th International Conference on Data Mining", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/cicn/2014/6929/0/6929a602", "title": "Clustering Categorical Data Using Rough Membership Function", "doi": null, "abstractUrl": "/proceedings-article/cicn/2014/6929a602/12OmNxveNF6", "parentPublication": { "id": "proceedings/cicn/2014/6929/0", "title": "2014 International Conference on Computational Intelligence and Communication Networks (CICN)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icdm/2008/3502/0/3502a343", "title": "SCS: A New Similarity Measure for Categorical Sequences", "doi": null, "abstractUrl": "/proceedings-article/icdm/2008/3502a343/12OmNzcPAam", "parentPublication": { "id": "proceedings/icdm/2008/3502/0", "title": "2008 Eighth IEEE International Conference on Data Mining", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tk/2014/10/06547142", "title": "A Novel Variable-order Markov Model for Clustering Categorical Sequences", "doi": null, "abstractUrl": "/journal/tk/2014/10/06547142/13rRUxlgxTQ", "parentPublication": { "id": "trans/tk", "title": "IEEE Transactions on Knowledge & Data Engineering", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/cvpr/2018/6420/0/642000i004", "title": "Unsupervised Domain Adaptation with Similarity Learning", "doi": null, "abstractUrl": "/proceedings-article/cvpr/2018/642000i004/17D45WLdYQI", "parentPublication": { "id": "proceedings/cvpr/2018/6420/0", "title": "2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "08017612", "articleId": "13rRUwkxc5r", "__typename": "AdjacentArticleType" }, "next": { "fno": "08019879", "articleId": "13rRUxAATgA", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [ { "id": "17ShDTXWRXU", "name": "ttg201801-08022969s1.zip", "location": "https://www.computer.org/csdl/api/v1/extra/ttg201801-08022969s1.zip", "extension": "zip", "size": "70.5 MB", "__typename": "WebExtraType" } ], "articleVideos": [] }
{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUxAATgA", "doi": "10.1109/TVCG.2017.2744938", "abstract": "Among the many types of deep models, deep generative models (DGMs) provide a solution to the important problem of unsupervised and semi-supervised learning. However, training DGMs requires more skill, experience, and know-how because their training is more complex than other types of deep models such as convolutional neural networks (CNNs). We develop a visual analytics approach for better understanding and diagnosing the training process of a DGM. To help experts understand the overall training process, we first extract a large amount of time series data that represents training dynamics (e.g., activation changes over time). A blue-noise polyline sampling scheme is then introduced to select time series samples, which can both preserve outliers and reduce visual clutter. To further investigate the root cause of a failed training process, we propose a credit assignment algorithm that indicates how other neurons contribute to the output of the neuron causing the training failure. Two case studies are conducted with machine learning experts to demonstrate how our approach helps understand and diagnose the training processes of DGMs. We also show how our approach can be directly used to analyze other types of deep models, such as CNNs.", "abstracts": [ { "abstractType": "Regular", "content": "Among the many types of deep models, deep generative models (DGMs) provide a solution to the important problem of unsupervised and semi-supervised learning. However, training DGMs requires more skill, experience, and know-how because their training is more complex than other types of deep models such as convolutional neural networks (CNNs). We develop a visual analytics approach for better understanding and diagnosing the training process of a DGM. To help experts understand the overall training process, we first extract a large amount of time series data that represents training dynamics (e.g., activation changes over time). A blue-noise polyline sampling scheme is then introduced to select time series samples, which can both preserve outliers and reduce visual clutter. To further investigate the root cause of a failed training process, we propose a credit assignment algorithm that indicates how other neurons contribute to the output of the neuron causing the training failure. Two case studies are conducted with machine learning experts to demonstrate how our approach helps understand and diagnose the training processes of DGMs. We also show how our approach can be directly used to analyze other types of deep models, such as CNNs.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Among the many types of deep models, deep generative models (DGMs) provide a solution to the important problem of unsupervised and semi-supervised learning. However, training DGMs requires more skill, experience, and know-how because their training is more complex than other types of deep models such as convolutional neural networks (CNNs). We develop a visual analytics approach for better understanding and diagnosing the training process of a DGM. To help experts understand the overall training process, we first extract a large amount of time series data that represents training dynamics (e.g., activation changes over time). A blue-noise polyline sampling scheme is then introduced to select time series samples, which can both preserve outliers and reduce visual clutter. To further investigate the root cause of a failed training process, we propose a credit assignment algorithm that indicates how other neurons contribute to the output of the neuron causing the training failure. Two case studies are conducted with machine learning experts to demonstrate how our approach helps understand and diagnose the training processes of DGMs. We also show how our approach can be directly used to analyze other types of deep models, such as CNNs.", "title": "Analyzing the Training Processes of Deep Generative Models", "normalizedTitle": "Analyzing the Training Processes of Deep Generative Models", "fno": "08019879", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Training", "Neurons", "Time Series Analysis", "Tools", "Visual Analytics", "Analytical Models", "Deep Learning", "Deep Generative Models", "Blue Noise Sampling", "Credit Assignment" ], "authors": [ { "givenName": "Mengchen", "surname": "Liu", "fullName": "Mengchen Liu", "affiliation": "Tsinghua UniversityNational Engineering Lab for Big Data Software", "__typename": "ArticleAuthorType" }, { "givenName": "Jiaxin", "surname": "Shi", "fullName": "Jiaxin Shi", "affiliation": "Tsinghua University", "__typename": "ArticleAuthorType" }, { "givenName": "Kelei", "surname": "Cao", "fullName": "Kelei Cao", "affiliation": "Tsinghua UniversityNational Engineering Lab for Big Data Software", "__typename": "ArticleAuthorType" }, { "givenName": "Jun", "surname": "Zhu", "fullName": "Jun Zhu", "affiliation": "Tsinghua University", "__typename": "ArticleAuthorType" }, { "givenName": "Shixia", "surname": "Liu", "fullName": "Shixia Liu", "affiliation": "Tsinghua UniversityNational Engineering Lab for Big Data Software", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "77-87", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/ipdpsw/2015/7684/0/7684b172", "title": "Scaling Up the Training of Deep CNNs for Human Action Recognition", 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"title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tp/2018/11/08081757", "title": "Max-Margin Deep Generative Models for (Semi-)Supervised Learning", "doi": null, "abstractUrl": "/journal/tp/2018/11/08081757/143fgZJUyze", "parentPublication": { "id": "trans/tp", "title": "IEEE Transactions on Pattern Analysis & Machine Intelligence", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iiswc/2018/6780/0/08573476", "title": "Benchmarking and Analyzing Deep Neural Network Training", "doi": null, "abstractUrl": "/proceedings-article/iiswc/2018/08573476/17D45WwsQ7r", "parentPublication": { "id": "proceedings/iiswc/2018/6780/0", "title": "2018 IEEE International Symposium on Workload Characterization (IISWC)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vast/2018/6861/0/08802509", 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{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUyogGAh", "doi": "10.1109/TVCG.2017.2744718", "abstract": "While deep learning models have achieved state-of-the-art accuracies for many prediction tasks, understanding these models remains a challenge. Despite the recent interest in developing visual tools to help users interpret deep learning models, the complexity and wide variety of models deployed in industry, and the large-scale datasets that they used, pose unique design challenges that are inadequately addressed by existing work. Through participatory design sessions with over 15 researchers and engineers at Facebook, we have developed, deployed, and iteratively improved ActiVis, an interactive visualization system for interpreting large-scale deep learning models and results. By tightly integrating multiple coordinated views, such as a computation graph overview of the model architecture, and a neuron activation view for pattern discovery and comparison, users can explore complex deep neural network models at both the instance-and subset-level. ActiVis has been deployed on Facebook's machine learning platform. We present case studies with Facebook researchers and engineers, and usage scenarios of how ActiVis may work with different models.", "abstracts": [ { "abstractType": "Regular", "content": "While deep learning models have achieved state-of-the-art accuracies for many prediction tasks, understanding these models remains a challenge. Despite the recent interest in developing visual tools to help users interpret deep learning models, the complexity and wide variety of models deployed in industry, and the large-scale datasets that they used, pose unique design challenges that are inadequately addressed by existing work. Through participatory design sessions with over 15 researchers and engineers at Facebook, we have developed, deployed, and iteratively improved ActiVis, an interactive visualization system for interpreting large-scale deep learning models and results. By tightly integrating multiple coordinated views, such as a computation graph overview of the model architecture, and a neuron activation view for pattern discovery and comparison, users can explore complex deep neural network models at both the instance-and subset-level. ActiVis has been deployed on Facebook's machine learning platform. We present case studies with Facebook researchers and engineers, and usage scenarios of how ActiVis may work with different models.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "While deep learning models have achieved state-of-the-art accuracies for many prediction tasks, understanding these models remains a challenge. Despite the recent interest in developing visual tools to help users interpret deep learning models, the complexity and wide variety of models deployed in industry, and the large-scale datasets that they used, pose unique design challenges that are inadequately addressed by existing work. Through participatory design sessions with over 15 researchers and engineers at Facebook, we have developed, deployed, and iteratively improved ActiVis, an interactive visualization system for interpreting large-scale deep learning models and results. By tightly integrating multiple coordinated views, such as a computation graph overview of the model architecture, and a neuron activation view for pattern discovery and comparison, users can explore complex deep neural network models at both the instance-and subset-level. ActiVis has been deployed on Facebook's machine learning platform. We present case studies with Facebook researchers and engineers, and usage scenarios of how ActiVis may work with different models.", "title": "A<sc>cti</sc>V<sc>is</sc>: Visual Exploration of Industry-Scale Deep Neural Network Models", "normalizedTitle": "ActiVis: Visual Exploration of Industry-Scale Deep Neural Network Models", "fno": "08022871", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Data Visualisation", "Learning Artificial Intelligence", "Neural Nets", "Visual Tools", "Large Scale Datasets", "Participatory Design Sessions", "Interactive Visualization System", "Large Scale Deep Learning Models", "Model Architecture", "Complex Deep Neural Network Models", "Visual Exploration", "Industry Scale Deep Neural Network Models", "Acti Vis System", "Machine Learning Platform", "Computational Modeling", "Tools", "Machine Learning", "Data Models", "Neurons", "Facebook", "Data Visualization", "Visual Analytics", "Deep Learning", "Machine Learning", "Information Visualization" ], "authors": [ { "givenName": "Minsuk", "surname": "Kahng", "fullName": "Minsuk Kahng", "affiliation": "Georgia Institute of Technology", "__typename": "ArticleAuthorType" }, { "givenName": "Pierre Y.", "surname": "Andrews", "fullName": "Pierre Y. Andrews", "affiliation": "Facebook", "__typename": "ArticleAuthorType" }, { "givenName": "Aditya", "surname": "Kalro", "fullName": "Aditya Kalro", "affiliation": "Facebook", "__typename": "ArticleAuthorType" }, { "givenName": "Duen Horng (Polo)", "surname": "Chau", "fullName": "Duen Horng (Polo) Chau", "affiliation": "Georgia Institute of Technology", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "88-97", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/aiccsa/2017/3581/0/3581a509", "title": "Facebook as a Learning Tool in Classrooms: A Case Study", "doi": null, "abstractUrl": "/proceedings-article/aiccsa/2017/3581a509/12OmNAqU4Tf", "parentPublication": { "id": "proceedings/aiccsa/2017/3581/0", "title": "2017 IEEE/ACS 14th International Conference on Computer Systems and Applications (AICCSA)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/fie/2013/5261/0/06684915", "title": "Adding social elements to game-based learning - An exploration", "doi": null, "abstractUrl": "/proceedings-article/fie/2013/06684915/12OmNsbY6Uu", "parentPublication": { "id": "proceedings/fie/2013/5261/0", "title": "2013 IEEE Frontiers in Education Conference (FIE)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/ic3/2018/6834/0/08530525", "title": "Invitation or Bait? 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{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUxlgxTs", "doi": "10.1109/TVCG.2017.2744358", "abstract": "Deep neural networks are now rivaling human accuracy in several pattern recognition problems. Compared to traditional classifiers, where features are handcrafted, neural networks learn increasingly complex features directly from the data. Instead of handcrafting the features, it is now the network architecture that is manually engineered. The network architecture parameters such as the number of layers or the number of filters per layer and their interconnections are essential for good performance. Even though basic design guidelines exist, designing a neural network is an iterative trial-and-error process that takes days or even weeks to perform due to the large datasets used for training. In this paper, we present DeepEyes, a Progressive Visual Analytics system that supports the design of neural networks during training. We present novel visualizations, supporting the identification of layers that learned a stable set of patterns and, therefore, are of interest for a detailed analysis. The system facilitates the identification of problems, such as superfluous filters or layers, and information that is not being captured by the network. We demonstrate the effectiveness of our system through multiple use cases, showing how a trained network can be compressed, reshaped and adapted to different problems.", "abstracts": [ { "abstractType": "Regular", "content": "Deep neural networks are now rivaling human accuracy in several pattern recognition problems. Compared to traditional classifiers, where features are handcrafted, neural networks learn increasingly complex features directly from the data. Instead of handcrafting the features, it is now the network architecture that is manually engineered. The network architecture parameters such as the number of layers or the number of filters per layer and their interconnections are essential for good performance. Even though basic design guidelines exist, designing a neural network is an iterative trial-and-error process that takes days or even weeks to perform due to the large datasets used for training. In this paper, we present DeepEyes, a Progressive Visual Analytics system that supports the design of neural networks during training. We present novel visualizations, supporting the identification of layers that learned a stable set of patterns and, therefore, are of interest for a detailed analysis. The system facilitates the identification of problems, such as superfluous filters or layers, and information that is not being captured by the network. We demonstrate the effectiveness of our system through multiple use cases, showing how a trained network can be compressed, reshaped and adapted to different problems.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Deep neural networks are now rivaling human accuracy in several pattern recognition problems. Compared to traditional classifiers, where features are handcrafted, neural networks learn increasingly complex features directly from the data. Instead of handcrafting the features, it is now the network architecture that is manually engineered. The network architecture parameters such as the number of layers or the number of filters per layer and their interconnections are essential for good performance. Even though basic design guidelines exist, designing a neural network is an iterative trial-and-error process that takes days or even weeks to perform due to the large datasets used for training. In this paper, we present DeepEyes, a Progressive Visual Analytics system that supports the design of neural networks during training. We present novel visualizations, supporting the identification of layers that learned a stable set of patterns and, therefore, are of interest for a detailed analysis. The system facilitates the identification of problems, such as superfluous filters or layers, and information that is not being captured by the network. We demonstrate the effectiveness of our system through multiple use cases, showing how a trained network can be compressed, reshaped and adapted to different problems.", "title": "DeepEyes: Progressive Visual Analytics for Designing Deep Neural Networks", "normalizedTitle": "DeepEyes: Progressive Visual Analytics for Designing Deep Neural Networks", "fno": "08019872", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Neurons", "Training", "Visual Analytics", "Neural Networks", "Three Dimensional Displays", "Layout", "Kernel", "Progressive Visual Analytics", "Deep Neural Networks", "Machine Learning" ], "authors": [ { "givenName": "Nicola", "surname": "Pezzotti", "fullName": "Nicola Pezzotti", "affiliation": "Intelligent Systems department, Delft University of Technology, Delft, The Netherlands", "__typename": "ArticleAuthorType" }, { "givenName": "Thomas", "surname": "Höllt", "fullName": "Thomas Höllt", "affiliation": "Intelligent Systems department, Delft University of Technology, Delft, The Netherlands", "__typename": "ArticleAuthorType" }, { "givenName": "Jan", "surname": "Van Gemert", "fullName": "Jan Van Gemert", "affiliation": "Intelligent Systems department, Delft University of Technology, Delft, The Netherlands", "__typename": "ArticleAuthorType" }, { "givenName": "Boudewijn P.F.", "surname": "Lelieveldt", "fullName": "Boudewijn P.F. Lelieveldt", "affiliation": "Department of Radiology, Division of Image Processing, Leiden University Medical Center, Leiden, The Netherlands", "__typename": "ArticleAuthorType" }, { "givenName": "Elmar", "surname": "Eisemann", "fullName": "Elmar Eisemann", "affiliation": "Intelligent Systems department, Delft University of Technology, Delft, The Netherlands", "__typename": "ArticleAuthorType" }, { "givenName": "Anna", "surname": "Vilanova", "fullName": "Anna Vilanova", "affiliation": "Intelligent Systems department, Delft University of Technology, Delft, The Netherlands", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "98-108", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "trans/tg/2016/01/07192683", "title": 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"abstractUrl": "/journal/tg/2021/02/09228894/1nYptLKl7by", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/tase/2020/4086/0/408600a073", "title": "Feature-oriented Design of Visual Analytics System for Interpretable Deep Learning based Intrusion Detection", "doi": null, "abstractUrl": "/proceedings-article/tase/2020/408600a073/1t0HAB8lCE0", "parentPublication": { "id": "proceedings/tase/2020/4086/0", "title": "2020 International Symposium on Theoretical Aspects of Software Engineering (TASE)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2022/12/09420254", "title": "Visual Analytics for RNN-Based Deep Reinforcement Learning", "doi": null, "abstractUrl": "/journal/tg/2022/12/09420254/1tdUMGe1DAk", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "08022871", "articleId": "13rRUyogGAh", "__typename": "AdjacentArticleType" }, "next": { "fno": "08019883", "articleId": "13rRUyv53Fz", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [ { "id": "17ShDTXWRT0", "name": "ttg201801-08019872s1.zip", "location": "https://www.computer.org/csdl/api/v1/extra/ttg201801-08019872s1.zip", "extension": "zip", "size": "43.4 MB", "__typename": "WebExtraType" } ], "articleVideos": [] }
{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUyv53Fz", "doi": "10.1109/TVCG.2017.2745178", "abstract": "In meteorology, cluster analysis is frequently used to determine representative trends in ensemble weather predictions in a selected spatio-temporal region, e.g., to reduce a set of ensemble members to simplify and improve their analysis. Identified clusters (i.e., groups of similar members), however, can be very sensitive to small changes of the selected region, so that clustering results can be misleading and bias subsequent analyses. In this article, we - a team of visualization scientists and meteorologists-deliver visual analytics solutions to analyze the sensitivity of clustering results with respect to changes of a selected region. We propose an interactive visual interface that enables simultaneous visualization of a) the variation in composition of identified clusters (i.e., their robustness), b) the variability in cluster membership for individual ensemble members, and c) the uncertainty in the spatial locations of identified trends. We demonstrate that our solution shows meteorologists how representative a clustering result is, and with respect to which changes in the selected region it becomes unstable. Furthermore, our solution helps to identify those ensemble members which stably belong to a given cluster and can thus be considered similar. In a real-world application case we show how our approach is used to analyze the clustering behavior of different regions in a forecast of &#x201C;Tropical Cyclone Karl&#x201D;, guiding the user towards the cluster robustness information required for subsequent ensemble analysis.", "abstracts": [ { "abstractType": "Regular", "content": "In meteorology, cluster analysis is frequently used to determine representative trends in ensemble weather predictions in a selected spatio-temporal region, e.g., to reduce a set of ensemble members to simplify and improve their analysis. Identified clusters (i.e., groups of similar members), however, can be very sensitive to small changes of the selected region, so that clustering results can be misleading and bias subsequent analyses. In this article, we - a team of visualization scientists and meteorologists-deliver visual analytics solutions to analyze the sensitivity of clustering results with respect to changes of a selected region. We propose an interactive visual interface that enables simultaneous visualization of a) the variation in composition of identified clusters (i.e., their robustness), b) the variability in cluster membership for individual ensemble members, and c) the uncertainty in the spatial locations of identified trends. We demonstrate that our solution shows meteorologists how representative a clustering result is, and with respect to which changes in the selected region it becomes unstable. Furthermore, our solution helps to identify those ensemble members which stably belong to a given cluster and can thus be considered similar. In a real-world application case we show how our approach is used to analyze the clustering behavior of different regions in a forecast of &#x201C;Tropical Cyclone Karl&#x201D;, guiding the user towards the cluster robustness information required for subsequent ensemble analysis.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "In meteorology, cluster analysis is frequently used to determine representative trends in ensemble weather predictions in a selected spatio-temporal region, e.g., to reduce a set of ensemble members to simplify and improve their analysis. Identified clusters (i.e., groups of similar members), however, can be very sensitive to small changes of the selected region, so that clustering results can be misleading and bias subsequent analyses. In this article, we - a team of visualization scientists and meteorologists-deliver visual analytics solutions to analyze the sensitivity of clustering results with respect to changes of a selected region. We propose an interactive visual interface that enables simultaneous visualization of a) the variation in composition of identified clusters (i.e., their robustness), b) the variability in cluster membership for individual ensemble members, and c) the uncertainty in the spatial locations of identified trends. We demonstrate that our solution shows meteorologists how representative a clustering result is, and with respect to which changes in the selected region it becomes unstable. Furthermore, our solution helps to identify those ensemble members which stably belong to a given cluster and can thus be considered similar. In a real-world application case we show how our approach is used to analyze the clustering behavior of different regions in a forecast of “Tropical Cyclone Karl”, guiding the user towards the cluster robustness information required for subsequent ensemble analysis.", "title": "Visualizing Confidence in Cluster-Based Ensemble Weather Forecast Analyses", "normalizedTitle": "Visualizing Confidence in Cluster-Based Ensemble Weather Forecast Analyses", "fno": "08019883", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Data Analysis", "Geophysics Computing", "Pattern Clustering", "Statistical Analysis", "Storms", "Weather Forecasting", "Ensemble Weather Forecast Analyses", "Ensemble Weather Predictions", "Interactive Visual Interface", "Simultaneous Visualization", "Cluster Membership", "Cluster Robustness Information", "Subsequent Ensemble Analysis", "Visual Analytics", "Ensemble Members", "Tropical Cyclone Karl", "Weather Forecasting", "Data Visualization", "Robustness", "Market Research", "Visualization", "Uncertainty", "Uncertainty Visualization", "Ensemble Visualization", "Clustering", "Meteorology" ], "authors": [ { "givenName": "Alexander", "surname": "Kumpf", "fullName": "Alexander Kumpf", "affiliation": "Computer Graphics & Visualization Group, Technische Universität München, Garching, Germany", "__typename": "ArticleAuthorType" }, { "givenName": "Bianca", "surname": "Tost", "fullName": "Bianca Tost", "affiliation": "Computer Graphics & Visualization Group, Technische Universität München, Garching, Germany", "__typename": "ArticleAuthorType" }, { "givenName": "Marlene", "surname": "Baumgart", "fullName": "Marlene Baumgart", "affiliation": "Institute of Atmospheric Physics, Johannes Gutenberg Universität Mainz, Mainz, Germany", "__typename": "ArticleAuthorType" }, { "givenName": "Michael", "surname": "Riemer", "fullName": "Michael Riemer", "affiliation": "Institute of Atmospheric Physics, Johannes Gutenberg Universität Mainz, Mainz, Germany", "__typename": "ArticleAuthorType" }, { "givenName": "Rüdiger", "surname": "Westermann", "fullName": "Rüdiger Westermann", "affiliation": "Computer Graphics & Visualization Group, Technische Universität München, Garching, Germany", "__typename": "ArticleAuthorType" }, { "givenName": "Marc", "surname": "Rautenhaus", "fullName": "Marc Rautenhaus", "affiliation": "Computer Graphics & Visualization Group, Technische Universität München, Garching, Germany", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "109-119", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/cad-graphics/2015/8020/0/07450406", "title": "A Visualization System for Weather Forecast Analogs", "doi": null, "abstractUrl": "/proceedings-article/cad-graphics/2015/07450406/12OmNqGRGim", "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/shpcc/1994/5680/0/00296669", "title": "Medium-range weather forecast on parallel systems", "doi": null, "abstractUrl": "/proceedings-article/shpcc/1994/00296669/12OmNwkzurx", "parentPublication": { "id": "proceedings/shpcc/1994/5680/0", "title": "Proceedings of IEEE Scalable High Performance Computing Conference", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2010/06/ttg2010061421", "title": "Noodles: A Tool for Visualization of Numerical Weather Model Ensemble Uncertainty", "doi": null, "abstractUrl": "/journal/tg/2010/06/ttg2010061421/13rRUILtJm4", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2018/01/08017585", "title": "Robust Detection and Visualization of Jet-Stream Core Lines in Atmospheric Flow", "doi": null, "abstractUrl": "/journal/tg/2018/01/08017585/13rRUwInvl6", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2017/01/07539342", "title": "Time-Hierarchical Clustering and Visualization of Weather Forecast Ensembles", "doi": null, "abstractUrl": "/journal/tg/2017/01/07539342/13rRUxYIN4d", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2016/01/07192710", "title": "Visually Comparing Weather Features in Forecasts", "doi": null, "abstractUrl": "/journal/tg/2016/01/07192710/13rRUxly95E", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/e-science/2018/9156/0/915600a415", "title": "DeepDownscale: A Deep Learning Strategy for High-Resolution Weather Forecast", "doi": null, "abstractUrl": "/proceedings-article/e-science/2018/915600a415/17D45WaTklN", "parentPublication": { "id": "proceedings/e-science/2018/9156/0", "title": "2018 IEEE 14th International Conference on e-Science (e-Science)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2019/01/08440052", "title": "An Interactive Framework for Visualization of Weather Forecast Ensembles", "doi": null, "abstractUrl": "/journal/tg/2019/01/08440052/17D45XDIXW9", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2019/01/08440839", "title": "Visual Analysis of the Temporal Evolution of Ensemble Forecast Sensitivities", "doi": null, "abstractUrl": "/journal/tg/2019/01/08440839/17D45XfSEST", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/mdm/2021/2845/0/284500a258", "title": "Ship path planning based on Deep Reinforcement Learning and weather forecast", "doi": null, "abstractUrl": "/proceedings-article/mdm/2021/284500a258/1v2QBWkBIhq", "parentPublication": { "id": "proceedings/mdm/2021/2845/0", "title": "2021 22nd IEEE International Conference on Mobile Data Management (MDM)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "08019872", "articleId": "13rRUxlgxTs", "__typename": "AdjacentArticleType" }, "next": { "fno": "08019867", "articleId": "13rRUxD9gXO", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [ { "id": "17ShDTYet4x", "name": "ttg201801-08019883s1.zip", "location": "https://www.computer.org/csdl/api/v1/extra/ttg201801-08019883s1.zip", "extension": "zip", "size": "60.4 MB", "__typename": "WebExtraType" } ], "articleVideos": [] }
{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUxD9gXO", "doi": "10.1109/TVCG.2017.2744805", "abstract": "Clustering is a core building block for data analysis, aiming to extract otherwise hidden structures and relations from raw datasets, such as particular groups that can be effectively related, compared, and interpreted. A plethora of visual-interactive cluster analysis techniques has been proposed to date, however, arriving at useful clusterings often requires several rounds of user interactions to fine-tune the data preprocessing and algorithms. We present a multi-stage Visual Analytics (VA) approach for iterative cluster refinement together with an implementation (SOMFlow) that uses Self-Organizing Maps (SOM) to analyze time series data. It supports exploration by offering the analyst a visual platform to analyze intermediate results, adapt the underlying computations, iteratively partition the data, and to reflect previous analytical activities. The history of previous decisions is explicitly visualized within a flow graph, allowing to compare earlier cluster refinements and to explore relations. We further leverage quality and interestingness measures to guide the analyst in the discovery of useful patterns, relations, and data partitions. We conducted two pair analytics experiments together with a subject matter expert in speech intonation research to demonstrate that the approach is effective for interactive data analysis, supporting enhanced understanding of clustering results as well as the interactive process itself.", "abstracts": [ { "abstractType": "Regular", "content": "Clustering is a core building block for data analysis, aiming to extract otherwise hidden structures and relations from raw datasets, such as particular groups that can be effectively related, compared, and interpreted. A plethora of visual-interactive cluster analysis techniques has been proposed to date, however, arriving at useful clusterings often requires several rounds of user interactions to fine-tune the data preprocessing and algorithms. We present a multi-stage Visual Analytics (VA) approach for iterative cluster refinement together with an implementation (SOMFlow) that uses Self-Organizing Maps (SOM) to analyze time series data. It supports exploration by offering the analyst a visual platform to analyze intermediate results, adapt the underlying computations, iteratively partition the data, and to reflect previous analytical activities. The history of previous decisions is explicitly visualized within a flow graph, allowing to compare earlier cluster refinements and to explore relations. We further leverage quality and interestingness measures to guide the analyst in the discovery of useful patterns, relations, and data partitions. We conducted two pair analytics experiments together with a subject matter expert in speech intonation research to demonstrate that the approach is effective for interactive data analysis, supporting enhanced understanding of clustering results as well as the interactive process itself.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Clustering is a core building block for data analysis, aiming to extract otherwise hidden structures and relations from raw datasets, such as particular groups that can be effectively related, compared, and interpreted. A plethora of visual-interactive cluster analysis techniques has been proposed to date, however, arriving at useful clusterings often requires several rounds of user interactions to fine-tune the data preprocessing and algorithms. We present a multi-stage Visual Analytics (VA) approach for iterative cluster refinement together with an implementation (SOMFlow) that uses Self-Organizing Maps (SOM) to analyze time series data. It supports exploration by offering the analyst a visual platform to analyze intermediate results, adapt the underlying computations, iteratively partition the data, and to reflect previous analytical activities. The history of previous decisions is explicitly visualized within a flow graph, allowing to compare earlier cluster refinements and to explore relations. We further leverage quality and interestingness measures to guide the analyst in the discovery of useful patterns, relations, and data partitions. We conducted two pair analytics experiments together with a subject matter expert in speech intonation research to demonstrate that the approach is effective for interactive data analysis, supporting enhanced understanding of clustering results as well as the interactive process itself.", "title": "SOMFlow: Guided Exploratory Cluster Analysis with Self-Organizing Maps and Analytic Provenance", "normalizedTitle": "SOMFlow: Guided Exploratory Cluster Analysis with Self-Organizing Maps and Analytic Provenance", "fno": "08019867", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Data Visualization", "Visualization", "Time Series Analysis", "Clustering Algorithms", "Self Organizing Feature Maps", "Algorithm Design And Analysis", "Speech", "Visual Analytics", "Interaction", "Visual Cluster Analysis", "Quality Metrics", "Guidance", "Self Organizing Maps", "Time Series" ], "authors": [ { "givenName": "Dominik", "surname": "Sacha", "fullName": "Dominik Sacha", "affiliation": "University of Konstanz, Germany", "__typename": "ArticleAuthorType" }, { "givenName": "Matthias", "surname": "Kraus", "fullName": "Matthias Kraus", "affiliation": "University of Konstanz, Germany", "__typename": "ArticleAuthorType" }, { "givenName": "Jürgen", "surname": "Bernard", "fullName": "Jürgen Bernard", "affiliation": "TU Darmstadt, Germany", "__typename": "ArticleAuthorType" }, { "givenName": "Michael", "surname": "Behrisch", "fullName": "Michael Behrisch", "affiliation": "University of Konstanz, Germany", "__typename": "ArticleAuthorType" }, { "givenName": "Tobias", "surname": "Schreck", "fullName": "Tobias Schreck", "affiliation": "Graz University of Technology", "__typename": "ArticleAuthorType" }, { "givenName": "Yuki", "surname": "Asano", "fullName": "Yuki Asano", "affiliation": "University of Tübingen", "__typename": "ArticleAuthorType" }, { "givenName": "Daniel A.", "surname": "Keim", "fullName": "Daniel A. Keim", "affiliation": "University of Konstanz, Germany", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "120-130", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/cmv/2005/2396/0/23960063", "title": "Exploration of Dimensionality Reduction for Text Visualization", "doi": null, "abstractUrl": "/proceedings-article/cmv/2005/23960063/12OmNCmGNXT", "parentPublication": { "id": "proceedings/cmv/2005/2396/0", "title": "Proceedings. Third International Conference on Coordinated and Multiple Views in Exploratory Visualization (CMV 2005)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icais/2009/3827/0/3827a108", "title": "Adapting to Increasing Data Availability Using Multi-layered Self-Organising Maps", "doi": null, "abstractUrl": "/proceedings-article/icais/2009/3827a108/12OmNrEL2A0", "parentPublication": { "id": "proceedings/icais/2009/3827/0", "title": "2009 International Conference on Adaptive and Intelligent Systems. ICAIS 2009", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/cseworkshops/2008/3257/0/3257a053", "title": "Combining Parallel Self-Organizing Maps and K-Means to Cluster Distributed Data", "doi": null, "abstractUrl": "/proceedings-article/cseworkshops/2008/3257a053/12OmNvkpl05", "parentPublication": { "id": "proceedings/cseworkshops/2008/3257/0", "title": "2008 11th IEEE International Conference on Computational Science and Engineering - Workshops", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iwcse/2009/3881/2/3881b535", "title": "Case Retrieval Method Based on Clustering Algorithm", "doi": null, "abstractUrl": "/proceedings-article/iwcse/2009/3881b535/12OmNvonIG1", "parentPublication": { "id": "proceedings/iwcse/2009/3881/2", "title": "Computer Science and Engineering, International Workshop on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/ipdps/2003/1926/0/19260154b", "title": "Gene Clustering Using Self-Organizing Maps and Particle Swarm Optimization", "doi": null, "abstractUrl": "/proceedings-article/ipdps/2003/19260154b/12OmNwsNRgL", "parentPublication": { "id": "proceedings/ipdps/2003/1926/0", "title": "Parallel and Distributed Processing Symposium, International", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/itng/2011/4367/0/4367a839", "title": "Patent Service Self-Organizing Maps", "doi": null, "abstractUrl": "/proceedings-article/itng/2011/4367a839/12OmNyQYt80", "parentPublication": { "id": "proceedings/itng/2011/4367/0", "title": "Information Technology: New Generations, Third International Conference on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/trustcom-bigdatase/2018/4388/0/438801b870", "title": "Monitoring Blockchains with Self-Organizing Maps", "doi": null, "abstractUrl": "/proceedings-article/trustcom-bigdatase/2018/438801b870/17D45WHONrJ", "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": "mags/cg/2019/06/08788592", "title": "Analytic Provenance in Practice: The Role of Provenance in Real-World Visualization and Data Analysis Environments", "doi": null, "abstractUrl": "/magazine/cg/2019/06/08788592/1cfqCMPtgRy", "parentPublication": { "id": "mags/cg", "title": "IEEE Computer Graphics and Applications", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vast/2019/2284/0/08986940", "title": "FDive: Learning Relevance Models Using Pattern-based Similarity Measures", "doi": null, "abstractUrl": "/proceedings-article/vast/2019/08986940/1hrMzTneKuA", "parentPublication": { "id": "proceedings/vast/2019/2284/0", "title": "2019 IEEE Conference on Visual Analytics Science and Technology (VAST)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iv/2020/9134/0/913400a644", "title": "hSOM: Visualizing Self-Organizing Maps to Accomodate Categorical Data", "doi": null, "abstractUrl": "/proceedings-article/iv/2020/913400a644/1rSR9OtfR1m", "parentPublication": { "id": "proceedings/iv/2020/9134/0", "title": "2020 24th International Conference Information Visualisation (IV)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "08019883", "articleId": "13rRUyv53Fz", "__typename": "AdjacentArticleType" }, "next": { "fno": "08019882", "articleId": "13rRUIJuxvq", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [ { "id": "17ShDTXWRG2", "name": "ttg201801-08019867s1.zip", "location": "https://www.computer.org/csdl/api/v1/extra/ttg201801-08019867s1.zip", "extension": "zip", "size": "55.8 MB", "__typename": "WebExtraType" } ], "articleVideos": [] }
{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUIJuxvq", "doi": "10.1109/TVCG.2017.2745258", "abstract": "Dimension reduction algorithms and clustering algorithms are both frequently used techniques in visual analytics. Both families of algorithms assist analysts in performing related tasks regarding the similarity of observations and finding groups in datasets. Though initially used independently, recent works have incorporated algorithms from each family into the same visualization systems. However, these algorithmic combinations are often ad hoc or disconnected, working independently and in parallel rather than integrating some degree of interdependence. A number of design decisions must be addressed when employing dimension reduction and clustering algorithms concurrently in a visualization system, including the selection of each algorithm, the order in which they are processed, and how to present and interact with the resulting projection. This paper contributes an overview of combining dimension reduction and clustering into a visualization system, discussing the challenges inherent in developing a visualization system that makes use of both families of algorithms.", "abstracts": [ { "abstractType": "Regular", "content": "Dimension reduction algorithms and clustering algorithms are both frequently used techniques in visual analytics. Both families of algorithms assist analysts in performing related tasks regarding the similarity of observations and finding groups in datasets. Though initially used independently, recent works have incorporated algorithms from each family into the same visualization systems. However, these algorithmic combinations are often ad hoc or disconnected, working independently and in parallel rather than integrating some degree of interdependence. A number of design decisions must be addressed when employing dimension reduction and clustering algorithms concurrently in a visualization system, including the selection of each algorithm, the order in which they are processed, and how to present and interact with the resulting projection. This paper contributes an overview of combining dimension reduction and clustering into a visualization system, discussing the challenges inherent in developing a visualization system that makes use of both families of algorithms.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Dimension reduction algorithms and clustering algorithms are both frequently used techniques in visual analytics. Both families of algorithms assist analysts in performing related tasks regarding the similarity of observations and finding groups in datasets. Though initially used independently, recent works have incorporated algorithms from each family into the same visualization systems. However, these algorithmic combinations are often ad hoc or disconnected, working independently and in parallel rather than integrating some degree of interdependence. A number of design decisions must be addressed when employing dimension reduction and clustering algorithms concurrently in a visualization system, including the selection of each algorithm, the order in which they are processed, and how to present and interact with the resulting projection. This paper contributes an overview of combining dimension reduction and clustering into a visualization system, discussing the challenges inherent in developing a visualization system that makes use of both families of algorithms.", "title": "Towards a Systematic Combination of Dimension Reduction and Clustering in Visual Analytics", "normalizedTitle": "Towards a Systematic Combination of Dimension Reduction and Clustering in Visual Analytics", "fno": "08019882", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Clustering Algorithms", "Algorithm Design And Analysis", "Data Visualization", "Partitioning Algorithms", "Visualization", "Manifolds", "Dimension Reduction", "Clustering", "Algorithms", "Visual Analytics" ], "authors": [ { "givenName": "John", "surname": "Wenskovitch", "fullName": "John Wenskovitch", "affiliation": "Virginia Tech Department of Computer Science", "__typename": "ArticleAuthorType" }, { "givenName": "Ian", "surname": "Crandell", "fullName": "Ian Crandell", "affiliation": "Virginia Tech Department of Statistics", "__typename": "ArticleAuthorType" }, { "givenName": "Naren", "surname": "Ramakrishnan", "fullName": "Naren Ramakrishnan", "affiliation": "Virginia Tech Department of Computer Science", "__typename": "ArticleAuthorType" }, { "givenName": "Leanna", "surname": "House", "fullName": "Leanna House", "affiliation": "Virginia Tech Department of Statistics", "__typename": "ArticleAuthorType" }, { "givenName": "Scotland", "surname": "Leman", "fullName": "Scotland Leman", "affiliation": "Virginia Tech Department of Statistics", "__typename": "ArticleAuthorType" }, { "givenName": "Chris", "surname": "North", "fullName": "Chris North", "affiliation": "Virginia Tech Department of Computer Science", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "131-141", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/iccvw/2011/0063/0/06130412", "title": "A invertible dimension reduction of curves on a manifold", "doi": null, "abstractUrl": "/proceedings-article/iccvw/2011/06130412/12OmNAFFdEL", "parentPublication": { "id": "proceedings/iccvw/2011/0063/0", "title": "2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icpr/2008/2174/0/04761130", "title": "Metric Learning: A general dimension reduction framework for classification and visualization", "doi": null, "abstractUrl": "/proceedings-article/icpr/2008/04761130/12OmNAlNiGe", "parentPublication": { "id": "proceedings/icpr/2008/2174/0", "title": "ICPR 2008 19th International Conference on Pattern Recognition", "__typename": "ParentPublication" }, "__typename": 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"/journal/tg/2018/01/08019866/13rRUwInv4t", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tb/2015/04/06915894", "title": "ClusterViz: A Cytoscape APP for Cluster Analysis of Biological Network", "doi": null, "abstractUrl": "/journal/tb/2015/04/06915894/13rRUxbCbrZ", "parentPublication": { "id": "trans/tb", "title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vis/2022/8812/0/881200a075", "title": "Parametric Dimension Reduction by Preserving Local Structure", "doi": null, "abstractUrl": "/proceedings-article/vis/2022/881200a075/1J6henXuhws", "parentPublication": { "id": "proceedings/vis/2022/8812/0", "title": "2022 IEEE Visualization and Visual Analytics (VIS)", "__typename": "ParentPublication" }, 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International Conference on Pattern Recognition (ICPR)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/ispa-bdcloud-socialcom-sustaincom/2020/1485/0/148500a948", "title": "Topic Clustering Using Induced Squared Correlation Thresholding with Dimension Reduction", "doi": null, "abstractUrl": "/proceedings-article/ispa-bdcloud-socialcom-sustaincom/2020/148500a948/1ua4LOE4e7S", "parentPublication": { "id": "proceedings/ispa-bdcloud-socialcom-sustaincom/2020/1485/0", "title": "2020 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "08019867", "articleId": "13rRUxD9gXO", "__typename": "AdjacentArticleType" }, "next": { "fno": "08019866", "articleId": 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{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUwInv4t", "doi": "10.1109/TVCG.2017.2745085", "abstract": "Clustering, the process of grouping together similar items into distinct partitions, is a common type of unsupervised machine learning that can be useful for summarizing and aggregating complex multi-dimensional data. However, data can be clustered in many ways, and there exist a large body of algorithms designed to reveal different patterns. While having access to a wide variety of algorithms is helpful, in practice, it is quite difficult for data scientists to choose and parameterize algorithms to get the clustering results relevant for their dataset and analytical tasks. To alleviate this problem, we built Clustervision, a visual analytics tool that helps ensure data scientists find the right clustering among the large amount of techniques and parameters available. Our system clusters data using a variety of clustering techniques and parameters and then ranks clustering results utilizing five quality metrics. In addition, users can guide the system to produce more relevant results by providing task-relevant constraints on the data. Our visual user interface allows users to find high quality clustering results, explore the clusters using several coordinated visualization techniques, and select the cluster result that best suits their task. We demonstrate this novel approach using a case study with a team of researchers in the medical domain and showcase that our system empowers users to choose an effective representation of their complex data.", "abstracts": [ { "abstractType": "Regular", "content": "Clustering, the process of grouping together similar items into distinct partitions, is a common type of unsupervised machine learning that can be useful for summarizing and aggregating complex multi-dimensional data. However, data can be clustered in many ways, and there exist a large body of algorithms designed to reveal different patterns. While having access to a wide variety of algorithms is helpful, in practice, it is quite difficult for data scientists to choose and parameterize algorithms to get the clustering results relevant for their dataset and analytical tasks. To alleviate this problem, we built Clustervision, a visual analytics tool that helps ensure data scientists find the right clustering among the large amount of techniques and parameters available. Our system clusters data using a variety of clustering techniques and parameters and then ranks clustering results utilizing five quality metrics. In addition, users can guide the system to produce more relevant results by providing task-relevant constraints on the data. Our visual user interface allows users to find high quality clustering results, explore the clusters using several coordinated visualization techniques, and select the cluster result that best suits their task. We demonstrate this novel approach using a case study with a team of researchers in the medical domain and showcase that our system empowers users to choose an effective representation of their complex data.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Clustering, the process of grouping together similar items into distinct partitions, is a common type of unsupervised machine learning that can be useful for summarizing and aggregating complex multi-dimensional data. However, data can be clustered in many ways, and there exist a large body of algorithms designed to reveal different patterns. While having access to a wide variety of algorithms is helpful, in practice, it is quite difficult for data scientists to choose and parameterize algorithms to get the clustering results relevant for their dataset and analytical tasks. To alleviate this problem, we built Clustervision, a visual analytics tool that helps ensure data scientists find the right clustering among the large amount of techniques and parameters available. Our system clusters data using a variety of clustering techniques and parameters and then ranks clustering results utilizing five quality metrics. In addition, users can guide the system to produce more relevant results by providing task-relevant constraints on the data. Our visual user interface allows users to find high quality clustering results, explore the clusters using several coordinated visualization techniques, and select the cluster result that best suits their task. We demonstrate this novel approach using a case study with a team of researchers in the medical domain and showcase that our system empowers users to choose an effective representation of their complex data.", "title": "Clustervision: Visual Supervision of Unsupervised Clustering", "normalizedTitle": "Clustervision: Visual Supervision of Unsupervised Clustering", "fno": "08019866", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Clustering Algorithms", "Measurement", "Visual Analytics", "Partitioning Algorithms", "Data Visualization", "Indexes", "Unsupervised Clustering", "Visual Analytics", "Quality Metrics", "Interactive Visual Clustering" ], "authors": [ { "givenName": "Bum Chul", "surname": "Kwon", "fullName": "Bum Chul Kwon", "affiliation": "IBM T.J. Watson Research Center, NY, USA", "__typename": "ArticleAuthorType" }, { "givenName": "Ben", "surname": "Eysenbach", "fullName": "Ben Eysenbach", "affiliation": "Massachusetts Institute of Technology, Cambridge, MA, USA", "__typename": "ArticleAuthorType" }, { "givenName": "Janu", "surname": "Verma", "fullName": "Janu Verma", "affiliation": "IBM T.J. Watson Research Center, NY, USA", "__typename": "ArticleAuthorType" }, { "givenName": "Kenney", "surname": "Ng", "fullName": "Kenney Ng", "affiliation": "IBM T.J. Watson Research Center, NY, USA", "__typename": "ArticleAuthorType" }, { "givenName": "Christopher", "surname": "De Filippi", "fullName": "Christopher De Filippi", "affiliation": "Inova Heart and Vascular Institute, Fairfax, VA, USA", "__typename": "ArticleAuthorType" }, { "givenName": "Walter F.", "surname": "Stewart", "fullName": "Walter F. Stewart", "affiliation": "Sutter Health Research, Walnut Creek, California, USA", "__typename": "ArticleAuthorType" }, { "givenName": "Adam", "surname": "Perer", "fullName": "Adam Perer", "affiliation": "IBM T.J. Watson Research Center, NY, USA", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "142-151", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/vast/2014/6227/0/07042514", "title": "Visual analysis of missing data — To see what isn't there", "doi": null, "abstractUrl": "/proceedings-article/vast/2014/07042514/12OmNxzMnNA", "parentPublication": { "id": "proceedings/vast/2014/6227/0", "title": "2014 IEEE Conference on Visual Analytics Science and Technology (VAST)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/synasc/2012/5026/0/06481030", "title": "Variable Density Based Genetic Clustering", "doi": null, "abstractUrl": "/proceedings-article/synasc/2012/06481030/12OmNzahbYD", "parentPublication": { "id": "proceedings/synasc/2012/5026/0", "title": "2012 14th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "mags/cg/2009/02/mcg2009020014", "title": "Defining Insight for Visual Analytics", "doi": null, "abstractUrl": "/magazine/cg/2009/02/mcg2009020014/13rRUwh80JN", "parentPublication": { "id": "mags/cg", "title": "IEEE Computer Graphics and Applications", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "mags/cg/2012/04/mcg2012040063", "title": "The Top 10 Challenges in Extreme-Scale Visual Analytics", "doi": null, "abstractUrl": "/magazine/cg/2012/04/mcg2012040063/13rRUxC0SGA", "parentPublication": { "id": "mags/cg", "title": "IEEE Computer Graphics and Applications", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2013/12/ttg2013122179", "title": "Visual Analytics for Spatial Clustering: Using a Heuristic Approach for Guided Exploration", "doi": null, "abstractUrl": "/journal/tg/2013/12/ttg2013122179/13rRUyeTVi3", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2012/12/ttg2012122829", "title": "Scatter/Gather Clustering: Flexibly Incorporating User Feedback to Steer Clustering Results", "doi": null, "abstractUrl": "/journal/tg/2012/12/ttg2012122829/13rRUypp57E", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2019/01/08440035", "title": "Clustrophile 2: Guided Visual Clustering Analysis", "doi": null, "abstractUrl": "/journal/tg/2019/01/08440035/17D45WnnFYU", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vds/2022/5721/0/572100a001", "title": "Case Study Comparison of Computational Notebook Platforms for Interactive Visual Analytics", "doi": null, "abstractUrl": "/proceedings-article/vds/2022/572100a001/1JezLhI4Vm8", "parentPublication": { "id": "proceedings/vds/2022/5721/0", "title": "2022 IEEE Visualization in Data Science (VDS)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/aiotcs/2022/3410/0/341000a206", "title": "Data Mining Analysis of New Energy Vehicles Based on Constrained Clustering Algorithm", "doi": null, "abstractUrl": "/proceedings-article/aiotcs/2022/341000a206/1MuZOoZmef6", "parentPublication": { "id": "proceedings/aiotcs/2022/3410/0", "title": "2022 International Conference on Artificial Intelligence of Things and Crowdsensing (AIoTCs)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2021/02/09237999", "title": "Integrating Prior Knowledge in Mixed-Initiative Social Network Clustering", "doi": null, "abstractUrl": "/journal/tg/2021/02/09237999/1oa15tKyG9W", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "08019882", "articleId": "13rRUIJuxvq", "__typename": "AdjacentArticleType" }, "next": { "fno": "08017618", "articleId": "13rRUwghd55", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [ { "id": "17ShDTXFgEH", "name": "ttg201801-08019866s1.zip", "location": "https://www.computer.org/csdl/api/v1/extra/ttg201801-08019866s1.zip", "extension": "zip", "size": "81.9 MB", "__typename": "WebExtraType" } ], "articleVideos": [] }
{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUwghd55", "doi": "10.1109/TVCG.2017.2744683", "abstract": "Convolutional Neural Networks (CNNs) currently achieve state-of-the-art accuracy in image classification. With a growing number of classes, the accuracy usually drops as the possibilities of confusion increase. Interestingly, the class confusion patterns follow a hierarchical structure over the classes. We present visual-analytics methods to reveal and analyze this hierarchy of similar classes in relation with CNN-internal data. We found that this hierarchy not only dictates the confusion patterns between the classes, it furthermore dictates the learning behavior of CNNs. In particular, the early layers in these networks develop feature detectors that can separate high-level groups of classes quite well, even after a few training epochs. In contrast, the latter layers require substantially more epochs to develop specialized feature detectors that can separate individual classes. We demonstrate how these insights are key to significant improvement in accuracy by designing hierarchy-aware CNNs that accelerate model convergence and alleviate overfitting. We further demonstrate how our methods help in identifying various quality issues in the training data.", "abstracts": [ { "abstractType": "Regular", "content": "Convolutional Neural Networks (CNNs) currently achieve state-of-the-art accuracy in image classification. With a growing number of classes, the accuracy usually drops as the possibilities of confusion increase. Interestingly, the class confusion patterns follow a hierarchical structure over the classes. We present visual-analytics methods to reveal and analyze this hierarchy of similar classes in relation with CNN-internal data. We found that this hierarchy not only dictates the confusion patterns between the classes, it furthermore dictates the learning behavior of CNNs. In particular, the early layers in these networks develop feature detectors that can separate high-level groups of classes quite well, even after a few training epochs. In contrast, the latter layers require substantially more epochs to develop specialized feature detectors that can separate individual classes. We demonstrate how these insights are key to significant improvement in accuracy by designing hierarchy-aware CNNs that accelerate model convergence and alleviate overfitting. We further demonstrate how our methods help in identifying various quality issues in the training data.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Convolutional Neural Networks (CNNs) currently achieve state-of-the-art accuracy in image classification. With a growing number of classes, the accuracy usually drops as the possibilities of confusion increase. Interestingly, the class confusion patterns follow a hierarchical structure over the classes. We present visual-analytics methods to reveal and analyze this hierarchy of similar classes in relation with CNN-internal data. We found that this hierarchy not only dictates the confusion patterns between the classes, it furthermore dictates the learning behavior of CNNs. In particular, the early layers in these networks develop feature detectors that can separate high-level groups of classes quite well, even after a few training epochs. In contrast, the latter layers require substantially more epochs to develop specialized feature detectors that can separate individual classes. We demonstrate how these insights are key to significant improvement in accuracy by designing hierarchy-aware CNNs that accelerate model convergence and alleviate overfitting. We further demonstrate how our methods help in identifying various quality issues in the training data.", "title": "Do Convolutional Neural Networks Learn Class Hierarchy?", "normalizedTitle": "Do Convolutional Neural Networks Learn Class Hierarchy?", "fno": "08017618", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Data Visualization", "Training", "Neurons", "Feature Extraction", "Training Data", "Image Recognition", "Convolutional Neural Networks", "Deep Learning", "Image Classification", "Large Scale Classification", "Confusion Matrix" ], "authors": [ { "givenName": "Alsallakh", "surname": "Bilal", "fullName": "Alsallakh Bilal", "affiliation": "Bosch Research North AmericaPalo Alto, CA", "__typename": "ArticleAuthorType" }, { "givenName": "Amin", "surname": "Jourabloo", "fullName": "Amin Jourabloo", "affiliation": "Michigan State University", "__typename": "ArticleAuthorType" }, { "givenName": "Mao", "surname": "Ye", "fullName": "Mao Ye", "affiliation": "Bosch Research North AmericaPalo Alto, CA", "__typename": "ArticleAuthorType" }, { "givenName": "Xiaoming", "surname": "Liu", "fullName": "Xiaoming Liu", "affiliation": "Michigan State University", "__typename": "ArticleAuthorType" }, { "givenName": "Liu", "surname": "Ren", "fullName": "Liu Ren", "affiliation": "Bosch Research North AmericaPalo Alto, CA", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "152-162", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/iccvw/2015/9711/0/5720a019", "title": "Do Deep Neural Networks Learn Facial Action Units When Doing Expression Recognition?", "doi": null, "abstractUrl": "/proceedings-article/iccvw/2015/5720a019/12OmNvsDHJg", "parentPublication": { "id": "proceedings/iccvw/2015/9711/0", "title": "2015 IEEE International Conference on Computer Vision Workshop (ICCVW)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icfhr/2016/0981/0/0981a193", "title": "On the Benefits of Convolutional Neural Network Combinations in Offline Handwriting Recognition", "doi": null, "abstractUrl": "/proceedings-article/icfhr/2016/0981a193/12OmNwGqBo2", "parentPublication": { "id": "proceedings/icfhr/2016/0981/0", "title": "2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icpr/2012/2216/0/06460220", "title": "Cascaded heterogeneous convolutional neural networks for handwritten digit recognition", "doi": null, "abstractUrl": "/proceedings-article/icpr/2012/06460220/12OmNwc3wsJ", "parentPublication": { "id": "proceedings/icpr/2012/2216/0", "title": "2012 21st International Conference on Pattern Recognition (ICPR 2012)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iccv/2015/8391/0/8391c740", "title": "HD-CNN: Hierarchical Deep Convolutional Neural Networks for Large Scale Visual Recognition", "doi": null, "abstractUrl": "/proceedings-article/iccv/2015/8391c740/12OmNxZkht1", "parentPublication": { "id": "proceedings/iccv/2015/8391/0", "title": "2015 IEEE International Conference on Computer Vision (ICCV)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/cvpr/2014/5118/0/5118b717", "title": "Learning and Transferring Mid-level Image Representations Using Convolutional Neural Networks", "doi": null, "abstractUrl": "/proceedings-article/cvpr/2014/5118b717/12OmNxcvh5p", "parentPublication": { "id": "proceedings/cvpr/2014/5118/0", "title": "2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/aipr/2017/1235/0/08457965", "title": "The poor generalization of deep convolutional networks to aerial imagery from new geographic locations: an empirical study with solar array detection", "doi": null, "abstractUrl": "/proceedings-article/aipr/2017/08457965/13xI8A8WyXm", "parentPublication": { "id": "proceedings/aipr/2017/1235/0", "title": "2017 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/aipr/2017/1235/0/08457960", "title": "The poor generalization of deep convolutional networks to aerial imagery from new geographic locations: an empirical study with solar array detection", "doi": null, "abstractUrl": "/proceedings-article/aipr/2017/08457960/13xI8AH0qyZ", "parentPublication": { "id": "proceedings/aipr/2017/1235/0", "title": "2017 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)", "__typename": "ParentPublication" }, "__typename": 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Classification of Images", "doi": null, "abstractUrl": "/proceedings-article/big-data/2020/09378237/1s647oEI7cs", "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": "08019866", "articleId": "13rRUwInv4t", "__typename": "AdjacentArticleType" }, "next": { "fno": "08017582", "articleId": "13rRUwj7cph", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [ { "id": "17ShDTXFgxH", "name": "ttg201801-08017618s1.zip", "location": "https://www.computer.org/csdl/api/v1/extra/ttg201801-08017618s1.zip", "extension": "zip", "size": "72 MB", "__typename": "WebExtraType" } ], "articleVideos": [] }
{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUwj7cph", "doi": "10.1109/TVCG.2017.2744378", "abstract": "Tree boosting, which combines weak learners (typically decision trees) to generate a strong learner, is a highly effective and widely used machine learning method. However, the development of a high performance tree boosting model is a time-consuming process that requires numerous trial-and-error experiments. To tackle this issue, we have developed a visual diagnosis tool, BOOSTVis, to help experts quickly analyze and diagnose the training process of tree boosting. In particular, we have designed a temporal confusion matrix visualization, and combined it with a t-SNE projection and a tree visualization. These visualization components work together to provide a comprehensive overview of a tree boosting model, and enable an effective diagnosis of an unsatisfactory training process. Two case studies that were conducted on the Otto Group Product Classification Challenge dataset demonstrate that BOOSTVis can provide informative feedback and guidance to improve understanding and diagnosis of tree boosting algorithms.", "abstracts": [ { "abstractType": "Regular", "content": "Tree boosting, which combines weak learners (typically decision trees) to generate a strong learner, is a highly effective and widely used machine learning method. However, the development of a high performance tree boosting model is a time-consuming process that requires numerous trial-and-error experiments. To tackle this issue, we have developed a visual diagnosis tool, BOOSTVis, to help experts quickly analyze and diagnose the training process of tree boosting. In particular, we have designed a temporal confusion matrix visualization, and combined it with a t-SNE projection and a tree visualization. These visualization components work together to provide a comprehensive overview of a tree boosting model, and enable an effective diagnosis of an unsatisfactory training process. Two case studies that were conducted on the Otto Group Product Classification Challenge dataset demonstrate that BOOSTVis can provide informative feedback and guidance to improve understanding and diagnosis of tree boosting algorithms.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Tree boosting, which combines weak learners (typically decision trees) to generate a strong learner, is a highly effective and widely used machine learning method. However, the development of a high performance tree boosting model is a time-consuming process that requires numerous trial-and-error experiments. To tackle this issue, we have developed a visual diagnosis tool, BOOSTVis, to help experts quickly analyze and diagnose the training process of tree boosting. In particular, we have designed a temporal confusion matrix visualization, and combined it with a t-SNE projection and a tree visualization. These visualization components work together to provide a comprehensive overview of a tree boosting model, and enable an effective diagnosis of an unsatisfactory training process. Two case studies that were conducted on the Otto Group Product Classification Challenge dataset demonstrate that BOOSTVis can provide informative feedback and guidance to improve understanding and diagnosis of tree boosting algorithms.", "title": "Visual Diagnosis of Tree Boosting Methods", "normalizedTitle": "Visual Diagnosis of Tree Boosting Methods", "fno": "08017582", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Data Visualisation", "Decision Trees", "Image Classification", "Learning Artificial Intelligence", "Time Consuming Process", "Visual Diagnosis Tool", "Temporal Confusion Matrix Visualization", "Tree Visualization", "Visualization Components", "Tree Boosting Model", "Unsatisfactory Training Process", "Tree Boosting Algorithms", "Tree Boosting Methods", "Typically Decision Trees", "Machine Learning Method", "Boosting", "Training", "Decision Trees", "Tools", "Vegetation", "Visualization", "Analytical Models", "Tree Boosting", "Model Analysis", "Temporal Confusion Matrix", "Tree Visualization" ], "authors": [ { "givenName": "Shixia", "surname": "Liu", "fullName": "Shixia Liu", "affiliation": "Tsinghua University and National Engineering Lab for Big Data Software", "__typename": "ArticleAuthorType" }, { "givenName": "Jiannan", "surname": "Xiao", "fullName": "Jiannan Xiao", "affiliation": "Tsinghua University and National Engineering Lab for Big Data Software", "__typename": "ArticleAuthorType" }, { "givenName": "Junlin", "surname": "Liu", "fullName": "Junlin Liu", "affiliation": "Tsinghua University and National Engineering Lab for Big Data Software", "__typename": "ArticleAuthorType" }, { "givenName": "Xiting", "surname": "Wang", "fullName": "Xiting Wang", "affiliation": "Microsoft Research", "__typename": "ArticleAuthorType" }, { "givenName": "Jing", "surname": "Wu", "fullName": "Jing Wu", "affiliation": "Cardiff University", "__typename": "ArticleAuthorType" }, { "givenName": "Jun", "surname": "Zhu", "fullName": "Jun Zhu", "affiliation": "Tsinghua University and National Engineering Lab for Big Data Software", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": false, "showRecommendedArticles": true, "isOpenAccess": true, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "163-173", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/tai/1998/5214/0/00744846", "title": "Integrating boosting and stochastic attribute selection committees for further improving the performance of decision tree learning", "doi": null, "abstractUrl": "/proceedings-article/tai/1998/00744846/12OmNrJAe5Q", "parentPublication": { "id": "proceedings/tai/1998/5214/0", "title": "Proceedings of 10th International Conference on Tools with Artificial Intelligence (ICTA'98)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iciev/2013/0400/0/06572718", 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"/journal/tp/2014/05/06583153/13rRUwbaqW2", "parentPublication": { "id": "trans/tp", "title": "IEEE Transactions on Pattern Analysis & Machine Intelligence", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/bigdatasecurity-hpsc-ids/2017/6296/0/07980351", "title": "A Taxi Gap Prediction Method via Double Ensemble Gradient Boosting Decision Tree", "doi": null, "abstractUrl": "/proceedings-article/bigdatasecurity-hpsc-ids/2017/07980351/17D45XeKgqx", "parentPublication": { "id": "proceedings/bigdatasecurity-hpsc-ids/2017/6296/0", "title": "2017 IEEE 3rd International Conference on Big Data Security on Cloud (BigDataSecurity), IEEE International Conference on High Performance and Smart Computing, (HPSC) and IEEE International Conference on Intelligent Data and Security (IDS)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/cluster/2019/4734/0/08890990", "title": "HarpGBDT: Optimizing Gradient Boosting Decision Tree for Parallel Efficiency", "doi": null, "abstractUrl": "/proceedings-article/cluster/2019/08890990/1eLymHVQenC", "parentPublication": { "id": "proceedings/cluster/2019/4734/0", "title": "2019 IEEE International Conference on Cluster Computing (CLUSTER)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/bracis/2019/4253/0/425300a132", "title": "Online Local Boosting: Improving Performance in Online Decision Trees", "doi": null, "abstractUrl": "/proceedings-article/bracis/2019/425300a132/1fHkFnNqR6o", "parentPublication": { "id": "proceedings/bracis/2019/4253/0", "title": "2019 8th Brazilian Conference on Intelligent Systems (BRACIS)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/big-data/2019/0858/0/09006028", "title": "Adapted Tree Boosting for Transfer Learning", "doi": null, "abstractUrl": "/proceedings-article/big-data/2019/09006028/1hJrKUE27yU", "parentPublication": { "id": "proceedings/big-data/2019/0858/0", "title": "2019 IEEE International Conference on Big Data (Big Data)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/pacificvis/2021/3931/0/393100a186", "title": "Investigating the Evolution of Tree Boosting Models with Visual Analytics", "doi": null, "abstractUrl": "/proceedings-article/pacificvis/2021/393100a186/1tTtslm0K4g", "parentPublication": { "id": "proceedings/pacificvis/2021/3931/0", "title": "2021 IEEE 14th Pacific Visualization Symposium (PacificVis)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/cds/2021/0428/0/042800a007", "title": "Ensemble Learning in Credit Card Fraud Detection Using Boosting Methods", "doi": null, "abstractUrl": "/proceedings-article/cds/2021/042800a007/1uZxuAfIS8E", "parentPublication": { "id": "proceedings/cds/2021/0428/0", "title": "2021 2nd International Conference on Computing 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{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUxYINfl", "doi": "10.1109/TVCG.2017.2745158", "abstract": "Balancing accuracy gains with other objectives such as interpretability is a key challenge when building decision trees. However, this process is difficult to automate because it involves know-how about the domain as well as the purpose of the model. This paper presents TreePOD, a new approach for sensitivity-aware model selection along trade-offs. TreePOD is based on exploring a large set of candidate trees generated by sampling the parameters of tree construction algorithms. Based on this set, visualizations of quantitative and qualitative tree aspects provide a comprehensive overview of possible tree characteristics. Along trade-offs between two objectives, TreePOD provides efficient selection guidance by focusing on Pareto-optimal tree candidates. TreePOD also conveys the sensitivities of tree characteristics on variations of selected parameters by extending the tree generation process with a full-factorial sampling. We demonstrate how TreePOD supports a variety of tasks involved in decision tree selection and describe its integration in a holistic workflow for building and selecting decision trees. For evaluation, we illustrate a case study for predicting critical power grid states, and we report qualitative feedback from domain experts in the energy sector. This feedback suggests that TreePOD enables users with and without statistical background a confident and efficient identification of suitable decision trees.", "abstracts": [ { "abstractType": "Regular", "content": "Balancing accuracy gains with other objectives such as interpretability is a key challenge when building decision trees. However, this process is difficult to automate because it involves know-how about the domain as well as the purpose of the model. This paper presents TreePOD, a new approach for sensitivity-aware model selection along trade-offs. TreePOD is based on exploring a large set of candidate trees generated by sampling the parameters of tree construction algorithms. Based on this set, visualizations of quantitative and qualitative tree aspects provide a comprehensive overview of possible tree characteristics. Along trade-offs between two objectives, TreePOD provides efficient selection guidance by focusing on Pareto-optimal tree candidates. TreePOD also conveys the sensitivities of tree characteristics on variations of selected parameters by extending the tree generation process with a full-factorial sampling. We demonstrate how TreePOD supports a variety of tasks involved in decision tree selection and describe its integration in a holistic workflow for building and selecting decision trees. For evaluation, we illustrate a case study for predicting critical power grid states, and we report qualitative feedback from domain experts in the energy sector. This feedback suggests that TreePOD enables users with and without statistical background a confident and efficient identification of suitable decision trees.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Balancing accuracy gains with other objectives such as interpretability is a key challenge when building decision trees. However, this process is difficult to automate because it involves know-how about the domain as well as the purpose of the model. This paper presents TreePOD, a new approach for sensitivity-aware model selection along trade-offs. TreePOD is based on exploring a large set of candidate trees generated by sampling the parameters of tree construction algorithms. Based on this set, visualizations of quantitative and qualitative tree aspects provide a comprehensive overview of possible tree characteristics. Along trade-offs between two objectives, TreePOD provides efficient selection guidance by focusing on Pareto-optimal tree candidates. TreePOD also conveys the sensitivities of tree characteristics on variations of selected parameters by extending the tree generation process with a full-factorial sampling. We demonstrate how TreePOD supports a variety of tasks involved in decision tree selection and describe its integration in a holistic workflow for building and selecting decision trees. For evaluation, we illustrate a case study for predicting critical power grid states, and we report qualitative feedback from domain experts in the energy sector. This feedback suggests that TreePOD enables users with and without statistical background a confident and efficient identification of suitable decision trees.", "title": "TreePOD: Sensitivity-Aware Selection of Pareto-Optimal Decision Trees", "normalizedTitle": "TreePOD: Sensitivity-Aware Selection of Pareto-Optimal Decision Trees", "fno": "08019878", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Decision Trees", "Vegetation", "Data Models", "Buildings", "Visualization", "Measurement", "Focusing", "Model Selection", "Classification Trees", "Visual Parameter Search", "Sensitivity Analysis", "Pareto Optimality" ], "authors": [ { "givenName": "Thomas", "surname": "Mühlbacher", "fullName": "Thomas Mühlbacher", "affiliation": "VRVis Research Center", "__typename": "ArticleAuthorType" }, { "givenName": "Lorenz", "surname": "Linhardt", "fullName": "Lorenz Linhardt", "affiliation": "ETH Zurich", "__typename": "ArticleAuthorType" }, { "givenName": "Torsten", "surname": "Möller", "fullName": "Torsten Möller", "affiliation": "University of Vienna", "__typename": "ArticleAuthorType" }, { "givenName": "Harald", "surname": "Piringer", "fullName": "Harald Piringer", "affiliation": "VRVis Research Center", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "174-183", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/fit/2015/9666/0/9666a012", "title": "Decision Trees Based Classification of Cardiotocograms Using Bagging Approach", "doi": null, "abstractUrl": "/proceedings-article/fit/2015/9666a012/12OmNARRYmU", "parentPublication": { "id": "proceedings/fit/2015/9666/0", "title": "2015 13th International Conference on Frontiers of Information Technology (FIT)", "__typename": "ParentPublication" }, 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"parentPublication": { "id": "trans/tk", "title": "IEEE Transactions on Knowledge & Data Engineering", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tp/1999/12/i1297", "title": "Globally Optimal Fuzzy Decision Trees for Classification and Regression", "doi": null, "abstractUrl": "/journal/tp/1999/12/i1297/13rRUxlgxUk", "parentPublication": { "id": "trans/tp", "title": "IEEE Transactions on Pattern Analysis & Machine Intelligence", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tk/2006/08/k1028", "title": "Orthogonal Decision Trees", "doi": null, "abstractUrl": "/journal/tk/2006/08/k1028/13rRUy2YLYT", "parentPublication": { "id": "trans/tk", "title": "IEEE Transactions on Knowledge & Data Engineering", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/ictai/2018/7449/0/744900a527", "title": "Random Forests with Stochastic Induction of Decision 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{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUxBa56b", "doi": "10.1109/TVCG.2017.2745280", "abstract": "We introduce the Dynamic Influence Network (DIN), a novel visual analytics technique for representing and analyzing rule-based models of protein-protein interaction networks. Rule-based modeling has proved instrumental in developing biological models that are concise, comprehensible, easily extensible, and that mitigate the combinatorial complexity of multi-state and multi-component biological molecules. Our technique visualizes the dynamics of these rules as they evolve over time. Using the data produced by KaSim, an open source stochastic simulator of rule-based models written in the Kappa language, DINs provide a node-link diagram that represents the influence that each rule has on the other rules. That is, rather than representing individual biological components or types, we instead represent the rules about them (as nodes) and the current influence of these rules (as links). Using our interactive DIN-Viz software tool, researchers are able to query this dynamic network to find meaningful patterns about biological processes, and to identify salient aspects of complex rule-based models. To evaluate the effectiveness of our approach, we investigate a simulation of a circadian clock model that illustrates the oscillatory behavior of the KaiC protein phosphorylation cycle.", "abstracts": [ { "abstractType": "Regular", "content": "We introduce the Dynamic Influence Network (DIN), a novel visual analytics technique for representing and analyzing rule-based models of protein-protein interaction networks. Rule-based modeling has proved instrumental in developing biological models that are concise, comprehensible, easily extensible, and that mitigate the combinatorial complexity of multi-state and multi-component biological molecules. Our technique visualizes the dynamics of these rules as they evolve over time. Using the data produced by KaSim, an open source stochastic simulator of rule-based models written in the Kappa language, DINs provide a node-link diagram that represents the influence that each rule has on the other rules. That is, rather than representing individual biological components or types, we instead represent the rules about them (as nodes) and the current influence of these rules (as links). Using our interactive DIN-Viz software tool, researchers are able to query this dynamic network to find meaningful patterns about biological processes, and to identify salient aspects of complex rule-based models. To evaluate the effectiveness of our approach, we investigate a simulation of a circadian clock model that illustrates the oscillatory behavior of the KaiC protein phosphorylation cycle.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "We introduce the Dynamic Influence Network (DIN), a novel visual analytics technique for representing and analyzing rule-based models of protein-protein interaction networks. Rule-based modeling has proved instrumental in developing biological models that are concise, comprehensible, easily extensible, and that mitigate the combinatorial complexity of multi-state and multi-component biological molecules. Our technique visualizes the dynamics of these rules as they evolve over time. Using the data produced by KaSim, an open source stochastic simulator of rule-based models written in the Kappa language, DINs provide a node-link diagram that represents the influence that each rule has on the other rules. That is, rather than representing individual biological components or types, we instead represent the rules about them (as nodes) and the current influence of these rules (as links). Using our interactive DIN-Viz software tool, researchers are able to query this dynamic network to find meaningful patterns about biological processes, and to identify salient aspects of complex rule-based models. To evaluate the effectiveness of our approach, we investigate a simulation of a circadian clock model that illustrates the oscillatory behavior of the KaiC protein phosphorylation cycle.", "title": "Dynamic Influence Networks for Rule-Based Models", "normalizedTitle": "Dynamic Influence Networks for Rule-Based Models", "fno": "08017593", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Biological System Modeling", "Data Visualization", "Analytical Models", "Proteins", "Computational Modeling", "Data Models", "Dynamic Networks", "Biological Data Visualization", "Rule Based Modeling", "Protein Protein Interaction Networks" ], "authors": [ { "givenName": "Angus G.", "surname": "Forbes", "fullName": "Angus G. Forbes", "affiliation": "University of California, Santa Cruz", "__typename": "ArticleAuthorType" }, { "givenName": "Andrew", "surname": "Burks", "fullName": "Andrew Burks", "affiliation": "University of Illinois, Chicago", "__typename": "ArticleAuthorType" }, { "givenName": "Kristine", "surname": "Lee", "fullName": "Kristine Lee", "affiliation": "University of Illinois, Chicago", "__typename": "ArticleAuthorType" }, { "givenName": "Xing", "surname": "Li", "fullName": "Xing Li", "affiliation": "University of Illinois, Chicago", "__typename": "ArticleAuthorType" }, { "givenName": "Pierre", "surname": "Boutillier", "fullName": "Pierre Boutillier", "affiliation": "Harvard Medical School", "__typename": "ArticleAuthorType" }, { "givenName": "Jean", "surname": "Krivine", "fullName": "Jean Krivine", "affiliation": "Université Paris Diderot", "__typename": "ArticleAuthorType" }, { "givenName": "Walter", "surname": "Fontana", "fullName": "Walter Fontana", "affiliation": "Harvard Medical School", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "184-194", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/bibm/2017/3050/0/08217997", "title": "TrapRM: Transcriptomic and proteomic rule mining using weighted shortest distance based multiple minimum supports for multi-omics dataset", "doi": null, "abstractUrl": "/proceedings-article/bibm/2017/08217997/12OmNqFrGL8", "parentPublication": { "id": "proceedings/bibm/2017/3050/0", "title": "2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/dexa/2014/5721/0/06974818", "title": "Protein Data Modelling for Concurrent Sequential 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{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUxASuAA", "doi": "10.1109/TVCG.2017.2744458", "abstract": "Discovering and analyzing biclusters, i.e., two sets of related entities with close relationships, is a critical task in many real-world applications, such as exploring entity co-occurrences in intelligence analysis, and studying gene expression in bio-informatics. While the output of biclustering techniques can offer some initial low-level insights, visual approaches are required on top of that due to the algorithmic output complexity. This paper proposes a visualization technique, called BiDots, that allows analysts to interactively explore biclusters over multiple domains. BiDots overcomes several limitations of existing bicluster visualizations by encoding biclusters in a more compact and cluster-driven manner. A set of handy interactions is incorporated to support flexible analysis of biclustering results. More importantly, BiDots addresses the cases of weighted biclusters, which has been underexploited in the literature. The design of BiDots is grounded by a set of analytical tasks derived from previous work. We demonstrate its usefulness and effectiveness for exploring computed biclusters with an investigative document analysis task, in which suspicious people and activities are identified from a text corpus.", "abstracts": [ { "abstractType": "Regular", "content": "Discovering and analyzing biclusters, i.e., two sets of related entities with close relationships, is a critical task in many real-world applications, such as exploring entity co-occurrences in intelligence analysis, and studying gene expression in bio-informatics. While the output of biclustering techniques can offer some initial low-level insights, visual approaches are required on top of that due to the algorithmic output complexity. This paper proposes a visualization technique, called BiDots, that allows analysts to interactively explore biclusters over multiple domains. BiDots overcomes several limitations of existing bicluster visualizations by encoding biclusters in a more compact and cluster-driven manner. A set of handy interactions is incorporated to support flexible analysis of biclustering results. More importantly, BiDots addresses the cases of weighted biclusters, which has been underexploited in the literature. The design of BiDots is grounded by a set of analytical tasks derived from previous work. We demonstrate its usefulness and effectiveness for exploring computed biclusters with an investigative document analysis task, in which suspicious people and activities are identified from a text corpus.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Discovering and analyzing biclusters, i.e., two sets of related entities with close relationships, is a critical task in many real-world applications, such as exploring entity co-occurrences in intelligence analysis, and studying gene expression in bio-informatics. While the output of biclustering techniques can offer some initial low-level insights, visual approaches are required on top of that due to the algorithmic output complexity. This paper proposes a visualization technique, called BiDots, that allows analysts to interactively explore biclusters over multiple domains. BiDots overcomes several limitations of existing bicluster visualizations by encoding biclusters in a more compact and cluster-driven manner. A set of handy interactions is incorporated to support flexible analysis of biclustering results. More importantly, BiDots addresses the cases of weighted biclusters, which has been underexploited in the literature. The design of BiDots is grounded by a set of analytical tasks derived from previous work. We demonstrate its usefulness and effectiveness for exploring computed biclusters with an investigative document analysis task, in which suspicious people and activities are identified from a text corpus.", "title": "BiDots: Visual Exploration of Weighted Biclusters", "normalizedTitle": "BiDots: Visual Exploration of Weighted Biclusters", "fno": "08017581", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Visualization", "Algorithm Design And Analysis", "Organizations", "Data Mining", "Sparse Matrices", "Data Visualization", "Gene Expression", "Biclustering", "Coordinated Relationship Analysis", "Visual Analytics" ], "authors": [ { "givenName": "Jian", "surname": "Zhao", "fullName": "Jian Zhao", "affiliation": "FX Palo Alto Laboratory", "__typename": "ArticleAuthorType" }, { "givenName": "Maoyuan", "surname": "Sun", "fullName": "Maoyuan Sun", "affiliation": "University of Massachusetts, Dartmouth", "__typename": "ArticleAuthorType" }, { "givenName": "Francine", "surname": "Chen", "fullName": "Francine Chen", "affiliation": "FX Palo Alto Laboratory", "__typename": "ArticleAuthorType" }, { "givenName": "Patrick", "surname": "Chiu", "fullName": "Patrick Chiu", "affiliation": "FX Palo Alto Laboratory", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "195-204", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/dexa/2015/7581/0/07406268", "title": "A Hybrid Possibilistic Algorithm for Biclustering: Application to Microarray Data Analysis", "doi": null, "abstractUrl": "/proceedings-article/dexa/2015/07406268/12OmNB8kHX7", "parentPublication": { "id": "proceedings/dexa/2015/7581/0", "title": "2015 26th International Workshop on Database and Expert Systems Applications (DEXA)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icdm/2013/5108/0/5108a747", "title": "Discovering Non-redundant Overlapping Biclusters on Gene Expression Data", "doi": null, "abstractUrl": "/proceedings-article/icdm/2013/5108a747/12OmNB9t6mz", "parentPublication": { "id": "proceedings/icdm/2013/5108/0", "title": "2013 IEEE International Conference on Data Mining (ICDM)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icde/2009/3545/0/3545b219", "title": "Exploiting Domain Knowledge to Improve Biological Significance of Biclusters with Key Missing Genes", "doi": null, "abstractUrl": "/proceedings-article/icde/2009/3545b219/12OmNBhZ4r9", "parentPublication": { "id": "proceedings/icde/2009/3545/0", "title": "2009 IEEE 25th International Conference on Data Engineering", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/aina/2018/2195/0/219501b003", "title": "NBF: An FCA-Based Algorithm to Identify Negative Correlation Biclusters of DNA Microarray Data", "doi": null, "abstractUrl": "/proceedings-article/aina/2018/219501b003/12OmNwGIcvk", "parentPublication": { "id": "proceedings/aina/2018/2195/0", "title": "2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iccicc/2016/3846/0/07862071", "title": "Ensemble cuckoo search biclustering of the gene expression data", "doi": null, "abstractUrl": "/proceedings-article/iccicc/2016/07862071/12OmNxWLTwv", "parentPublication": { "id": "proceedings/iccicc/2016/3846/0", "title": "2016 IEEE 15th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/biotechno/2008/3191/0/3191a131", "title": "RN-Cluster: Discovering Coherent Biclusters Which is Robust to Noise", "doi": null, "abstractUrl": "/proceedings-article/biotechno/2008/3191a131/12OmNy7yEfy", "parentPublication": { "id": "proceedings/biotechno/2008/3191/0", "title": "International Conference on Biocomputation, Bioinformatics, and Biomedical Technologies", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tk/2011/04/ttk2011040568", "title": "Finding Correlated Biclusters from Gene Expression Data", "doi": null, "abstractUrl": "/journal/tk/2011/04/ttk2011040568/13rRUILLkvM", "parentPublication": { "id": "trans/tk", "title": "IEEE Transactions on Knowledge & Data Engineering", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tb/2012/02/ttb2012020560", "title": "Parallelized Evolutionary Learning for Detection of Biclusters in Gene Expression Data", "doi": null, "abstractUrl": "/journal/tb/2012/02/ttb2012020560/13rRUx0xPtP", "parentPublication": { "id": "trans/tb", "title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/bracis/2018/8023/0/802300a546", "title": "A Study of Biclustering Coherence Measures for Gene Expression Data", "doi": null, "abstractUrl": "/proceedings-article/bracis/2018/802300a546/17D45XeKgpT", "parentPublication": { "id": "proceedings/bracis/2018/8023/0", "title": "2018 7th Brazilian Conference on Intelligent Systems (BRACIS)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vis/2019/4941/0/08933546", "title": "Interactive Bicluster Aggregation in Bipartite Graphs", "doi": null, "abstractUrl": "/proceedings-article/vis/2019/08933546/1fTgJv5NwT6", "parentPublication": { "id": "proceedings/vis/2019/4941/0", "title": "2019 IEEE Visualization Conference (VIS)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], 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{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUwcAqql", "doi": "10.1109/TVCG.2017.2744080", "abstract": "Whether and how does the structure of family trees differ by ancestral traits over generations? This is a fundamental question regarding the structural heterogeneity of family trees for the multi-generational transmission research. However, previous work mostly focuses on parent-child scenarios due to the lack of proper tools to handle the complexity of extending the research to multi-generational processes. Through an iterative design study with social scientists and historians, we develop TreeEvo that assists users to generate and test empirical hypotheses for multi-generational research. TreeEvo summarizes and organizes family trees by structural features in a dynamic manner based on a traditional Sankey diagram. A pixel-based technique is further proposed to compactly encode trees with complex structures in each Sankey Node. Detailed information of trees is accessible through a space-efficient visualization with semantic zooming. Moreover, TreeEvo embeds Multinomial Logit Model (MLM) to examine statistical associations between tree structure and ancestral traits. We demonstrate the effectiveness and usefulness of TreeEvo through an in-depth case-study with domain experts using a real-world dataset (containing 54,128 family trees of 126,196 individuals).", "abstracts": [ { "abstractType": "Regular", "content": "Whether and how does the structure of family trees differ by ancestral traits over generations? This is a fundamental question regarding the structural heterogeneity of family trees for the multi-generational transmission research. However, previous work mostly focuses on parent-child scenarios due to the lack of proper tools to handle the complexity of extending the research to multi-generational processes. Through an iterative design study with social scientists and historians, we develop TreeEvo that assists users to generate and test empirical hypotheses for multi-generational research. TreeEvo summarizes and organizes family trees by structural features in a dynamic manner based on a traditional Sankey diagram. A pixel-based technique is further proposed to compactly encode trees with complex structures in each Sankey Node. Detailed information of trees is accessible through a space-efficient visualization with semantic zooming. Moreover, TreeEvo embeds Multinomial Logit Model (MLM) to examine statistical associations between tree structure and ancestral traits. We demonstrate the effectiveness and usefulness of TreeEvo through an in-depth case-study with domain experts using a real-world dataset (containing 54,128 family trees of 126,196 individuals).", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Whether and how does the structure of family trees differ by ancestral traits over generations? This is a fundamental question regarding the structural heterogeneity of family trees for the multi-generational transmission research. However, previous work mostly focuses on parent-child scenarios due to the lack of proper tools to handle the complexity of extending the research to multi-generational processes. Through an iterative design study with social scientists and historians, we develop TreeEvo that assists users to generate and test empirical hypotheses for multi-generational research. TreeEvo summarizes and organizes family trees by structural features in a dynamic manner based on a traditional Sankey diagram. A pixel-based technique is further proposed to compactly encode trees with complex structures in each Sankey Node. Detailed information of trees is accessible through a space-efficient visualization with semantic zooming. Moreover, TreeEvo embeds Multinomial Logit Model (MLM) to examine statistical associations between tree structure and ancestral traits. We demonstrate the effectiveness and usefulness of TreeEvo through an in-depth case-study with domain experts using a real-world dataset (containing 54,128 family trees of 126,196 individuals).", "title": "How Do Ancestral Traits Shape Family Trees Over Generations?", "normalizedTitle": "How Do Ancestral Traits Shape Family Trees Over Generations?", "fno": "08017631", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Tools", "Sociology", "Statistics", "Visual Analytics", "Scalability", "Animation", "Quantitative Social Science", "Design Study", "Multiple Tree Visualization", "Sankey Diagram" ], "authors": [ { "givenName": "Siwei", "surname": "Fu", "fullName": "Siwei Fu", "affiliation": "Hong Kong University of Science and Technology", "__typename": "ArticleAuthorType" }, { "givenName": "Hao", "surname": "Dong", "fullName": "Hao Dong", "affiliation": "Princeton University", "__typename": "ArticleAuthorType" }, { "givenName": "Weiwei", "surname": "Cui", "fullName": "Weiwei Cui", "affiliation": "Microsoft Research", "__typename": "ArticleAuthorType" }, { "givenName": "Jian", "surname": "Zhao", "fullName": "Jian Zhao", "affiliation": "FX Palo Alto Laboratory", "__typename": "ArticleAuthorType" }, { "givenName": "Huamin", "surname": "Qu", "fullName": "Huamin Qu", "affiliation": "Hong Kong University of Science and Technology", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "205-214", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/nicoint/2016/2305/0/2305a134", "title": "Parent-Child Product Design Based on Dynamic Programming about Family Child Left Behind", "doi": null, "abstractUrl": "/proceedings-article/nicoint/2016/2305a134/12OmNAY79m0", "parentPublication": { "id": "proceedings/nicoint/2016/2305/0", "title": "2016 Nicograph International (NicoInt)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/fie/2015/8454/0/07344359", "title": "First in the family: A comparison of first-generation and non-first-generation engineering college students", "doi": null, "abstractUrl": "/proceedings-article/fie/2015/07344359/12OmNAkWve1", "parentPublication": { "id": "proceedings/fie/2015/8454/0", "title": "2015 IEEE Frontiers in Education Conference (FIE)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/pacificvis/2014/2874/0/2874a348", "title": "Japanese Behavior in Visual Analytics of Temporal Daily Life Data", "doi": null, "abstractUrl": "/proceedings-article/pacificvis/2014/2874a348/12OmNvEQsfX", "parentPublication": { "id": "proceedings/pacificvis/2014/2874/0", "title": "2014 IEEE Pacific Visualization Symposium (PacificVis)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tb/2015/06/07103335", "title": "A Cooperative Co-Evolutionary Genetic Algorithm for Tree Scoring and Ancestral Genome Inference", "doi": null, "abstractUrl": "/journal/tb/2015/06/07103335/13rRUy0HYPK", "parentPublication": { "id": "trans/tb", "title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tb/2017/02/07434624", "title": "Building Ancestral Recombination Graphs for Whole Genomes", "doi": null, "abstractUrl": "/journal/tb/2017/02/07434624/13rRUyoPSVC", "parentPublication": { "id": "trans/tb", "title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vast/2018/6861/0/08802465", "title": "VAST Challenge 2018: Suspense at the Wildlife Preserve", "doi": null, "abstractUrl": 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{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUy0qnGp", "doi": "10.1109/TVCG.2017.2744898", "abstract": "Finding patterns in graphs has become a vital challenge in many domains from biological systems, network security, to finance (e.g., finding money laundering rings of bankers and business owners). While there is significant interest in graph databases and querying techniques, less research has focused on helping analysts make sense of underlying patterns within a group of subgraph results. Visualizing graph query results is challenging, requiring effective summarization of a large number of subgraphs, each having potentially shared node-values, rich node features, and flexible structure across queries. We present VIGOR, a novel interactive visual analytics system, for exploring and making sense of query results. VIGOR uses multiple coordinated views, leveraging different data representations and organizations to streamline analysts sensemaking process. VIGOR contributes: (1) an exemplar-based interaction technique, where an analyst starts with a specific result and relaxes constraints to find other similar results or starts with only the structure (i.e., without node value constraints), and adds constraints to narrow in on specific results; and (2) a novel feature-aware subgraph result summarization. Through a collaboration with Symantec, we demonstrate how VIGOR helps tackle real-world problems through the discovery of security blindspots in a cybersecurity dataset with over 11,000 incidents. We also evaluate VIGOR with a within-subjects study, demonstrating VIGOR's ease of use over a leading graph database management system, and its ability to help analysts understand their results at higher speed and make fewer errors.", "abstracts": [ { "abstractType": "Regular", "content": "Finding patterns in graphs has become a vital challenge in many domains from biological systems, network security, to finance (e.g., finding money laundering rings of bankers and business owners). While there is significant interest in graph databases and querying techniques, less research has focused on helping analysts make sense of underlying patterns within a group of subgraph results. Visualizing graph query results is challenging, requiring effective summarization of a large number of subgraphs, each having potentially shared node-values, rich node features, and flexible structure across queries. We present VIGOR, a novel interactive visual analytics system, for exploring and making sense of query results. VIGOR uses multiple coordinated views, leveraging different data representations and organizations to streamline analysts sensemaking process. VIGOR contributes: (1) an exemplar-based interaction technique, where an analyst starts with a specific result and relaxes constraints to find other similar results or starts with only the structure (i.e., without node value constraints), and adds constraints to narrow in on specific results; and (2) a novel feature-aware subgraph result summarization. Through a collaboration with Symantec, we demonstrate how VIGOR helps tackle real-world problems through the discovery of security blindspots in a cybersecurity dataset with over 11,000 incidents. We also evaluate VIGOR with a within-subjects study, demonstrating VIGOR's ease of use over a leading graph database management system, and its ability to help analysts understand their results at higher speed and make fewer errors.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Finding patterns in graphs has become a vital challenge in many domains from biological systems, network security, to finance (e.g., finding money laundering rings of bankers and business owners). While there is significant interest in graph databases and querying techniques, less research has focused on helping analysts make sense of underlying patterns within a group of subgraph results. Visualizing graph query results is challenging, requiring effective summarization of a large number of subgraphs, each having potentially shared node-values, rich node features, and flexible structure across queries. We present VIGOR, a novel interactive visual analytics system, for exploring and making sense of query results. VIGOR uses multiple coordinated views, leveraging different data representations and organizations to streamline analysts sensemaking process. VIGOR contributes: (1) an exemplar-based interaction technique, where an analyst starts with a specific result and relaxes constraints to find other similar results or starts with only the structure (i.e., without node value constraints), and adds constraints to narrow in on specific results; and (2) a novel feature-aware subgraph result summarization. Through a collaboration with Symantec, we demonstrate how VIGOR helps tackle real-world problems through the discovery of security blindspots in a cybersecurity dataset with over 11,000 incidents. We also evaluate VIGOR with a within-subjects study, demonstrating VIGOR's ease of use over a leading graph database management system, and its ability to help analysts understand their results at higher speed and make fewer errors.", "title": "VIGOR: Interactive Visual Exploration of Graph Query Results", "normalizedTitle": "VIGOR: Interactive Visual Exploration of Graph Query Results", "fno": "08019832", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Data Visualization", "Logic Gates", "Computer Security", "Database Systems", "Data Mining", "Visualization", "Graph Querying", "Subgraph Results", "Query Result Visualization" ], "authors": [ { "givenName": "Robert", "surname": "Pienta", "fullName": "Robert Pienta", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Fred", "surname": "Hohman", "fullName": "Fred Hohman", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Alex", "surname": "Endert", "fullName": "Alex Endert", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Acar", "surname": "Tamersoy", "fullName": "Acar Tamersoy", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Kevin", "surname": "Roundy", "fullName": "Kevin Roundy", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Chris", "surname": "Gates", "fullName": "Chris Gates", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Shamkant", "surname": "Navathe", "fullName": "Shamkant Navathe", "affiliation": null, "__typename": "ArticleAuthorType" }, { "givenName": "Duen Horng", "surname": "Chau", "fullName": "Duen Horng Chau", "affiliation": null, "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "215-225", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/icdmw/2014/4274/0/4274b203", "title": "RQL: A SQL-Like Query Language for Discovering Meaningful Rules", "doi": null, "abstractUrl": "/proceedings-article/icdmw/2014/4274b203/12OmNCm7BFu", "parentPublication": { "id": "proceedings/icdmw/2014/4274/0", "title": "2014 IEEE International Conference on Data Mining Workshop (ICDMW)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icdmw/2013/3142/0/3143b097", "title": "Demonstrating Interactive Multi-resolution Large Graph Exploration", "doi": null, "abstractUrl": "/proceedings-article/icdmw/2013/3143b097/12OmNqBtiSr", "parentPublication": { "id": "proceedings/icdmw/2013/3142/0", "title": "2013 IEEE 13th International Conference on Data Mining Workshops (ICDMW)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icdm/2014/4302/0/4302a983", "title": "Flow-Based 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"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/tg/2014/12/06875969", "title": "GLO-STIX: Graph-Level Operations for Specifying Techniques and Interactive eXploration", "doi": null, "abstractUrl": "/journal/tg/2014/12/06875969/13rRUwh80Hd", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tk/2006/11/k1441", "title": "Discovering Frequent Graph Patterns Using Disjoint Paths", "doi": null, "abstractUrl": "/journal/tk/2006/11/k1441/13rRUy3xY8u", "parentPublication": { "id": "trans/tk", "title": "IEEE Transactions on Knowledge & Data Engineering", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": 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"abstractUrl": "/proceedings-article/icse-companion/2021/121900a284/1sET7DNJQ4M", "parentPublication": { "id": "proceedings/icse-companion/2021/1219/0/", "title": "2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "08017631", "articleId": "13rRUwcAqql", "__typename": "AdjacentArticleType" }, "next": { "fno": "08019835", "articleId": "13rRUIJuxpD", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [], "articleVideos": [] }
{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUIJuxpD", "doi": "10.1109/TVCG.2017.2744843", "abstract": "Network visualizations, often in the form of node-link diagrams, are an effective means to understand relationships between entities, discover entities with interesting characteristics, and to identify clusters. While several existing tools allow users to visualize pre-defined networks, creating these networks from raw data remains a challenging task, often requiring users to program custom scripts or write complex SQL commands. Some existing tools also allow users to both visualize and model networks. Interaction techniques adopted by these tools often assume users know the exact conditions for defining edges in the resulting networks. This assumption may not always hold true, however. In cases where users do not know much about attributes in the dataset or when there are several attributes to choose from, users may not know which attributes they could use to formulate linking conditions. We propose an alternate interaction technique to model networks that allows users to demonstrate to the system a subset of nodes and links they wish to see in the resulting network. The system, in response, recommends conditions that can be used to model networks based on the specified nodes and links. In this paper, we show how such a demonstration-based interaction technique can be used to model networks by employing it in a prototype tool, Graphiti. Through multiple usage scenarios, we show how Graphiti not only allows users to model networks from a tabular dataset but also facilitates updating a pre-defined network with additional edge types.", "abstracts": [ { "abstractType": "Regular", "content": "Network visualizations, often in the form of node-link diagrams, are an effective means to understand relationships between entities, discover entities with interesting characteristics, and to identify clusters. While several existing tools allow users to visualize pre-defined networks, creating these networks from raw data remains a challenging task, often requiring users to program custom scripts or write complex SQL commands. Some existing tools also allow users to both visualize and model networks. Interaction techniques adopted by these tools often assume users know the exact conditions for defining edges in the resulting networks. This assumption may not always hold true, however. In cases where users do not know much about attributes in the dataset or when there are several attributes to choose from, users may not know which attributes they could use to formulate linking conditions. We propose an alternate interaction technique to model networks that allows users to demonstrate to the system a subset of nodes and links they wish to see in the resulting network. The system, in response, recommends conditions that can be used to model networks based on the specified nodes and links. In this paper, we show how such a demonstration-based interaction technique can be used to model networks by employing it in a prototype tool, Graphiti. Through multiple usage scenarios, we show how Graphiti not only allows users to model networks from a tabular dataset but also facilitates updating a pre-defined network with additional edge types.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Network visualizations, often in the form of node-link diagrams, are an effective means to understand relationships between entities, discover entities with interesting characteristics, and to identify clusters. While several existing tools allow users to visualize pre-defined networks, creating these networks from raw data remains a challenging task, often requiring users to program custom scripts or write complex SQL commands. Some existing tools also allow users to both visualize and model networks. Interaction techniques adopted by these tools often assume users know the exact conditions for defining edges in the resulting networks. This assumption may not always hold true, however. In cases where users do not know much about attributes in the dataset or when there are several attributes to choose from, users may not know which attributes they could use to formulate linking conditions. We propose an alternate interaction technique to model networks that allows users to demonstrate to the system a subset of nodes and links they wish to see in the resulting network. The system, in response, recommends conditions that can be used to model networks based on the specified nodes and links. In this paper, we show how such a demonstration-based interaction technique can be used to model networks by employing it in a prototype tool, Graphiti. Through multiple usage scenarios, we show how Graphiti not only allows users to model networks from a tabular dataset but also facilitates updating a pre-defined network with additional edge types.", "title": "Graphiti: Interactive Specification of Attribute-Based Edges for Network Modeling and Visualization", "normalizedTitle": "Graphiti: Interactive Specification of Attribute-Based Edges for Network Modeling and Visualization", "fno": "08019835", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Tools", "Data Visualization", "Joining Processes", "Data Models", "Prototypes", "Image Color Analysis", "Computational Modeling", "Network Modeling", "Visual Analytics", "User Interaction" ], "authors": [ { "givenName": "Arjun", "surname": "Srinivasan", "fullName": "Arjun Srinivasan", "affiliation": "Georgia Institute of Technology", "__typename": "ArticleAuthorType" }, { "givenName": "Hyunwoo", "surname": "Park", "fullName": "Hyunwoo Park", "affiliation": "The Ohio State University", "__typename": "ArticleAuthorType" }, { "givenName": "Alex", "surname": "Endert", "fullName": "Alex Endert", "affiliation": "Georgia Institute of Technology", "__typename": "ArticleAuthorType" }, { "givenName": "Rahul C.", "surname": "Basole", "fullName": "Rahul C. Basole", "affiliation": "Georgia Institute of Technology", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "226-235", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/ieee-infovis/2005/2790/0/01532151", "title": "Visualization of graphs with associated timeseries data", "doi": null, "abstractUrl": "/proceedings-article/ieee-infovis/2005/01532151/12OmNA1mbbA", "parentPublication": { "id": "proceedings/ieee-infovis/2005/2790/0", "title": "Information Visualization, IEEE Symposium on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/ivapp/2014/8132/0/07294450", "title": "Hardware-accelerated attribute mapping for interactive visualization of complex 3D trajectories", "doi": null, "abstractUrl": "/proceedings-article/ivapp/2014/07294450/12OmNBdru8w", "parentPublication": { "id": "proceedings/ivapp/2014/8132/0", "title": "2014 International Conference on Information Visualization Theory and Applications (IVAPP)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/nss/2009/3838/0/3838a130", "title": "Extended K-Anonymity Models Against Attribute Disclosure", "doi": null, "abstractUrl": "/proceedings-article/nss/2009/3838a130/12OmNBpEeJc", "parentPublication": { "id": "proceedings/nss/2009/3838/0", "title": "Network and System Security, International Conference on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/pacificvis/2014/2874/0/2874a253", "title": "Bridging the Gap of Network Management and Anomaly Detection through Interactive Visualization", "doi": null, "abstractUrl": "/proceedings-article/pacificvis/2014/2874a253/12OmNC8uRAg", "parentPublication": { "id": "proceedings/pacificvis/2014/2874/0", "title": "2014 IEEE Pacific Visualization Symposium (PacificVis)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/3dv/2017/2610/0/261001a640", "title": "Cross-Modal Attribute Transfer for Rescaling 3D Models", "doi": null, "abstractUrl": "/proceedings-article/3dv/2017/261001a640/12OmNs0C9Os", "parentPublication": { "id": "proceedings/3dv/2017/2610/0", "title": "2017 International Conference on 3D Vision (3DV)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iv/2010/7846/0/05571369", "title": "The Network Lens: Interactive Exploration of Multivariate Networks Using Visual Filtering", "doi": null, "abstractUrl": "/proceedings-article/iv/2010/05571369/12OmNxUMHny", "parentPublication": { "id": "proceedings/iv/2010/7846/0", "title": "2010 14th International Conference Information Visualisation", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/infvis/2005/9464/0/01532151", "title": "Visualization of graphs with associated timeseries data", "doi": null, "abstractUrl": "/proceedings-article/infvis/2005/01532151/12OmNy7Qfnd", "parentPublication": { "id": "proceedings/infvis/2005/9464/0", "title": "IEEE Symposium on Information Visualization (InfoVis 05)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/eisic/2016/2857/0/07870189", "title": "Providing Extensibility to Threat Modelling in Cloud-COVER’s Underlying Analysis Model", "doi": null, "abstractUrl": "/proceedings-article/eisic/2016/07870189/12OmNyQYtcg", "parentPublication": { "id": "proceedings/eisic/2016/2857/0", "title": "2016 European Intelligence and Security Informatics Conference (EISIC)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/cvpr/2017/0457/0/0457g156", "title": 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{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUxBJhmV", "doi": "10.1109/TVCG.2017.2744098", "abstract": "Many approaches for analyzing a high-dimensional dataset assume that the dataset contains specific structures, e.g., clusters in linear subspaces or non-linear manifolds. This yields a trial-and-error process to verify the appropriate model and parameters. This paper contributes an exploratory interface that supports visual identification of low-dimensional structures in a high-dimensional dataset, and facilitates the optimized selection of data models and configurations. Our key idea is to abstract a set of global and local feature descriptors from the neighborhood graph-based representation of the latent low-dimensional structure, such as pairwise geodesic distance (GD) among points and pairwise local tangent space divergence (LTSD) among pointwise local tangent spaces (LTS). We propose a new LTSD-GD view, which is constructed by mapping LTSD and GD to the Z_$x$_Z axis and Z_$y$_Z axis using 1D multidimensional scaling, respectively. Unlike traditional dimensionality reduction methods that preserve various kinds of distances among points, the LTSD-GD view presents the distribution of pointwise LTS (Z_$x$_Z axis) and the variation of LTS in structures (the combination of Z_$x$_Z axis and Z_$y$_Z axis). We design and implement a suite of visual tools for navigating and reasoning about intrinsic structures of a high-dimensional dataset. Three case studies verify the effectiveness of our approach.", "abstracts": [ { "abstractType": "Regular", "content": "Many approaches for analyzing a high-dimensional dataset assume that the dataset contains specific structures, e.g., clusters in linear subspaces or non-linear manifolds. This yields a trial-and-error process to verify the appropriate model and parameters. This paper contributes an exploratory interface that supports visual identification of low-dimensional structures in a high-dimensional dataset, and facilitates the optimized selection of data models and configurations. Our key idea is to abstract a set of global and local feature descriptors from the neighborhood graph-based representation of the latent low-dimensional structure, such as pairwise geodesic distance (GD) among points and pairwise local tangent space divergence (LTSD) among pointwise local tangent spaces (LTS). We propose a new LTSD-GD view, which is constructed by mapping LTSD and GD to the $x$ axis and $y$ axis using 1D multidimensional scaling, respectively. Unlike traditional dimensionality reduction methods that preserve various kinds of distances among points, the LTSD-GD view presents the distribution of pointwise LTS ($x$ axis) and the variation of LTS in structures (the combination of $x$ axis and $y$ axis). We design and implement a suite of visual tools for navigating and reasoning about intrinsic structures of a high-dimensional dataset. Three case studies verify the effectiveness of our approach.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Many approaches for analyzing a high-dimensional dataset assume that the dataset contains specific structures, e.g., clusters in linear subspaces or non-linear manifolds. This yields a trial-and-error process to verify the appropriate model and parameters. This paper contributes an exploratory interface that supports visual identification of low-dimensional structures in a high-dimensional dataset, and facilitates the optimized selection of data models and configurations. Our key idea is to abstract a set of global and local feature descriptors from the neighborhood graph-based representation of the latent low-dimensional structure, such as pairwise geodesic distance (GD) among points and pairwise local tangent space divergence (LTSD) among pointwise local tangent spaces (LTS). We propose a new LTSD-GD view, which is constructed by mapping LTSD and GD to the - axis and - axis using 1D multidimensional scaling, respectively. Unlike traditional dimensionality reduction methods that preserve various kinds of distances among points, the LTSD-GD view presents the distribution of pointwise LTS (- axis) and the variation of LTS in structures (the combination of - axis and - axis). We design and implement a suite of visual tools for navigating and reasoning about intrinsic structures of a high-dimensional dataset. Three case studies verify the effectiveness of our approach.", "title": "LDSScanner: Exploratory Analysis of Low-Dimensional Structures in High-Dimensional Datasets", "normalizedTitle": "LDSScanner: Exploratory Analysis of Low-Dimensional Structures in High-Dimensional Datasets", "fno": "08017645", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Manifolds", "Data Visualization", "Data Models", "Visualization", "Tools", "Analytical Models", "Principal Component Analysis", "High Dimensional Data", "Low Dimensional Structure", "Subspace", "Manifold", "Visual Exploration" ], "authors": [ { "givenName": "Jiazhi", "surname": "Xia", "fullName": "Jiazhi Xia", "affiliation": "Central South University", "__typename": "ArticleAuthorType" }, { "givenName": "Fenjin", "surname": "Ye", "fullName": "Fenjin Ye", "affiliation": "Central South University", "__typename": "ArticleAuthorType" }, { "givenName": "Wei", "surname": "Chen", "fullName": "Wei Chen", "affiliation": "Zhejiang University", "__typename": "ArticleAuthorType" }, { "givenName": "Yusi", "surname": "Wang", "fullName": "Yusi Wang", "affiliation": "Central South University", "__typename": "ArticleAuthorType" }, { "givenName": "Weifeng", "surname": "Chen", "fullName": "Weifeng Chen", "affiliation": "Zhejiang University of Finance & Economics", "__typename": "ArticleAuthorType" }, { "givenName": "Yuxin", "surname": "Ma", "fullName": "Yuxin Ma", "affiliation": "Zhejiang University", "__typename": "ArticleAuthorType" }, { "givenName": "Anthony K.H.", "surname": "Tung", "fullName": "Anthony K.H. Tung", "affiliation": "National University of Singapore", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "236-245", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/cvpr/2016/8851/0/8851f268", "title": "Trace Quotient Meets Sparsity: A Method for Learning Low Dimensional Image Representations", "doi": null, "abstractUrl": "/proceedings-article/cvpr/2016/8851f268/12OmNAL3BbY", "parentPublication": { "id": "proceedings/cvpr/2016/8851/0", "title": "2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2016/01/07192671", "title": "InterAxis: Steering Scatterplot Axes via Observation-Level 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{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUygT7n3", "doi": "10.1109/TVCG.2017.2744738", "abstract": "Skyline queries have wide-ranging applications in fields that involve multi-criteria decision making, including tourism, retail industry, and human resources. By automatically removing incompetent candidates, skyline queries allow users to focus on a subset of superior data items (i.e., the skyline), thus reducing the decision-making overhead. However, users are still required to interpret and compare these superior items manually before making a successful choice. This task is challenging because of two issues. First, people usually have fuzzy, unstable, and inconsistent preferences when presented with multiple candidates. Second, skyline queries do not reveal the reasons for the superiority of certain skyline points in a multi-dimensional space. To address these issues, we propose SkyLens, a visual analytic system aiming at revealing the superiority of skyline points from different perspectives and at different scales to aid users in their decision making. Two scenarios demonstrate the usefulness of SkyLens on two datasets with a dozen of attributes. A qualitative study is also conducted to show that users can efficiently accomplish skyline understanding and comparison tasks with SkyLens.", "abstracts": [ { "abstractType": "Regular", "content": "Skyline queries have wide-ranging applications in fields that involve multi-criteria decision making, including tourism, retail industry, and human resources. By automatically removing incompetent candidates, skyline queries allow users to focus on a subset of superior data items (i.e., the skyline), thus reducing the decision-making overhead. However, users are still required to interpret and compare these superior items manually before making a successful choice. This task is challenging because of two issues. First, people usually have fuzzy, unstable, and inconsistent preferences when presented with multiple candidates. Second, skyline queries do not reveal the reasons for the superiority of certain skyline points in a multi-dimensional space. To address these issues, we propose SkyLens, a visual analytic system aiming at revealing the superiority of skyline points from different perspectives and at different scales to aid users in their decision making. Two scenarios demonstrate the usefulness of SkyLens on two datasets with a dozen of attributes. A qualitative study is also conducted to show that users can efficiently accomplish skyline understanding and comparison tasks with SkyLens.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Skyline queries have wide-ranging applications in fields that involve multi-criteria decision making, including tourism, retail industry, and human resources. By automatically removing incompetent candidates, skyline queries allow users to focus on a subset of superior data items (i.e., the skyline), thus reducing the decision-making overhead. However, users are still required to interpret and compare these superior items manually before making a successful choice. This task is challenging because of two issues. First, people usually have fuzzy, unstable, and inconsistent preferences when presented with multiple candidates. Second, skyline queries do not reveal the reasons for the superiority of certain skyline points in a multi-dimensional space. To address these issues, we propose SkyLens, a visual analytic system aiming at revealing the superiority of skyline points from different perspectives and at different scales to aid users in their decision making. Two scenarios demonstrate the usefulness of SkyLens on two datasets with a dozen of attributes. A qualitative study is also conducted to show that users can efficiently accomplish skyline understanding and comparison tasks with SkyLens.", "title": "SkyLens: Visual Analysis of Skyline on Multi-Dimensional Data", "normalizedTitle": "SkyLens: Visual Analysis of Skyline on Multi-Dimensional Data", "fno": "08019873", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Urban Areas", "Decision Making", "Visual Analytics", "Measurement", "Industries", "Skyline Query", "Skyline Visualization", "Multi Dimensional Data", "Visual Analytics", "Multi Criteria Decision Making" ], "authors": [ { "givenName": "Xun", "surname": "Zhao", "fullName": "Xun Zhao", "affiliation": "Hong Kong University of Science and Technology", "__typename": "ArticleAuthorType" }, { "givenName": "Yanhong", "surname": "Wu", "fullName": "Yanhong Wu", "affiliation": "Hong Kong University of Science and Technology", "__typename": "ArticleAuthorType" }, { "givenName": "Weiwei", "surname": "Cui", "fullName": "Weiwei Cui", "affiliation": "Microsoft Research Asia", "__typename": "ArticleAuthorType" }, { "givenName": "Xinnan", "surname": "Du", "fullName": "Xinnan Du", "affiliation": "Hong Kong University of Science and Technology", "__typename": "ArticleAuthorType" }, { "givenName": "Yuan", "surname": "Chen", "fullName": "Yuan Chen", "affiliation": "Hong Kong University of Science and Technology", "__typename": "ArticleAuthorType" }, { "givenName": "Yong", "surname": "Wang", "fullName": "Yong Wang", "affiliation": "Hong Kong University of Science and Technology", "__typename": "ArticleAuthorType" }, { "givenName": "Dik Lun", "surname": "Lee", "fullName": "Dik Lun Lee", "affiliation": "Hong Kong University of Science and Technology", "__typename": "ArticleAuthorType" }, { "givenName": "Huamin", "surname": "Qu", "fullName": "Huamin Qu", "affiliation": "Hong Kong University of Science and Technology", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "246-255", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/icdew/2008/2161/0/04498313", "title": "Skyline-join in distributed databases", "doi": null, "abstractUrl": "/proceedings-article/icdew/2008/04498313/12OmNASraR9", "parentPublication": { "id": "proceedings/icdew/2008/2161/0", "title": "2008 IEEE 24th International Conference on Data Engineering Workshop", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icisa/2010/5942/0/05480364", "title": "Extended k-dominant Skyline in High Dimensional Space", "doi": null, "abstractUrl": "/proceedings-article/icisa/2010/05480364/12OmNC0guzl", "parentPublication": { "id": "proceedings/icisa/2010/5942/0", "title": "2010 International Conference on Information Science and Applications", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/apweb/2010/4012/0/4012a358", "title": "Skyline Minimum Vector", "doi": null, "abstractUrl": "/proceedings-article/apweb/2010/4012a358/12OmNC17hTE", "parentPublication": { "id": "proceedings/apweb/2010/4012/0", "title": "Conference, International Asia-Pacific Web", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/csse/2008/3336/4/3336g435", "title": "QBSQ: A Quad-Tree Based Algorithm for Skyline Query", "doi": null, "abstractUrl": "/proceedings-article/csse/2008/3336g435/12OmNqOwQJ3", "parentPublication": { "id": "csse/2008/3336/4", "title": "Computer Science and Software Engineering, International Conference on", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icde/2017/6543/0/6543a099", "title": "K-Dominant Skyline Join Queries: Extending the Join Paradigm to K-Dominant Skylines", "doi": null, "abstractUrl": "/proceedings-article/icde/2017/6543a099/12OmNyUFg2g", "parentPublication": { "id": "proceedings/icde/2017/6543/0", "title": "2017 IEEE 33rd International Conference on Data Engineering (ICDE)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vast/2017/3163/0/08585456", "title": "Visual Analysis for Multi-Spectral Images Comparisons", "doi": null, "abstractUrl": "/proceedings-article/vast/2017/08585456/17D45XreC5P", "parentPublication": { "id": "proceedings/vast/2017/3163/0", "title": "2017 IEEE Conference on Visual Analytics Science and Technology (VAST)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tk/2020/07/08663344", "title": "Top-<italic>k</italic> Dominating Queries on Skyline Groups", "doi": null, "abstractUrl": "/journal/tk/2020/07/08663344/18exlaKcvHq", "parentPublication": { "id": "trans/tk", "title": "IEEE Transactions on Knowledge & Data Engineering", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icde/2019/7474/0/747400c113", "title": "Efficient Parallel Skyline Query Processing for High-Dimensional Data", "doi": null, "abstractUrl": "/proceedings-article/icde/2019/747400c113/1aDT2u6GCxq", "parentPublication": { "id": "proceedings/icde/2019/7474/0", "title": "2019 IEEE 35th International Conference on Data Engineering (ICDE)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/acit-csii-bcd/2017/3302/0/3302a007", "title": "Computing Skyline Using Taxicab Geometry", "doi": null, "abstractUrl": "/proceedings-article/acit-csii-bcd/2017/3302a007/1cdOzUO9HIk", "parentPublication": { "id": "proceedings/acit-csii-bcd/2017/3302/0", "title": "2017 5th Intl Conf on Applied Computing and Information Technology/4th Intl Conf on Computational Science/Intelligence and Applied Informatics/2nd Intl Conf on Big Data, Cloud 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{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUxD9h5e", "doi": "10.1109/TVCG.2017.2744685", "abstract": "Visualizing outliers in massive datasets requires statistical pre-processing in order to reduce the scale of the problem to a size amenable to rendering systems like D3, Plotly or analytic systems like R or SAS. This paper presents a new algorithm, called hdoutliers, for detecting multidimensional outliers. It is unique for a) dealing with a mixture of categorical and continuous variables, b) dealing with big-p (many columns of data), c) dealing with big-Z_$n$_Z (many rows of data), d) dealing with outliers that mask other outliers, and e) dealing consistently with unidimensional and multidimensional datasets. Unlike ad hoc methods found in many machine learning papers, hdoutliers is based on a distributional model that allows outliers to be tagged with a probability. This critical feature reduces the likelihood of false discoveries.", "abstracts": [ { "abstractType": "Regular", "content": "Visualizing outliers in massive datasets requires statistical pre-processing in order to reduce the scale of the problem to a size amenable to rendering systems like D3, Plotly or analytic systems like R or SAS. This paper presents a new algorithm, called hdoutliers, for detecting multidimensional outliers. It is unique for a) dealing with a mixture of categorical and continuous variables, b) dealing with big-p (many columns of data), c) dealing with big-$n$ (many rows of data), d) dealing with outliers that mask other outliers, and e) dealing consistently with unidimensional and multidimensional datasets. Unlike ad hoc methods found in many machine learning papers, hdoutliers is based on a distributional model that allows outliers to be tagged with a probability. This critical feature reduces the likelihood of false discoveries.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Visualizing outliers in massive datasets requires statistical pre-processing in order to reduce the scale of the problem to a size amenable to rendering systems like D3, Plotly or analytic systems like R or SAS. This paper presents a new algorithm, called hdoutliers, for detecting multidimensional outliers. It is unique for a) dealing with a mixture of categorical and continuous variables, b) dealing with big-p (many columns of data), c) dealing with big-- (many rows of data), d) dealing with outliers that mask other outliers, and e) dealing consistently with unidimensional and multidimensional datasets. Unlike ad hoc methods found in many machine learning papers, hdoutliers is based on a distributional model that allows outliers to be tagged with a probability. This critical feature reduces the likelihood of false discoveries.", "title": "Visualizing Big Data Outliers Through Distributed Aggregation", "normalizedTitle": "Visualizing Big Data Outliers Through Distributed Aggregation", "fno": "08019881", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Anomaly Detection", "Gaussian Distribution", "Standards", "Sociology", "Robustness", "Covariance Matrices", "Outliers", "Anomalies" ], "authors": [ { "givenName": "Leland", "surname": "Wilkinson", "fullName": "Leland Wilkinson", "affiliation": "H2O.aiUIC", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "256-266", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/aiccsa/2017/3581/0/3581a704", "title": "A Comparison 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{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUwdrdSD", "doi": "10.1109/TVCG.2017.2745180", "abstract": "As Visual Analytics (VA) research grows and diversifies to encompass new systems, techniques, and use contexts, gaining a holistic view of analytic practices is becoming ever more challenging. However, such a view is essential for researchers and practitioners seeking to develop systems for broad audiences that span multiple domains. In this paper, we interpret VA research through the lens of Activity Theory (AT)—a framework for modelling human activities that has been influential in the field of Human-Computer Interaction. We first provide an overview of Activity Theory, showing its potential for thinking beyond tasks, representations, and interactions to the broader systems of activity in which interactive tools are embedded and used. Next, we describe how Activity Theory can be used as an organizing framework in the construction of activity typologies, building and expanding upon the tradition of abstract task taxonomies in the field of Information Visualization. We then apply the resulting process to create an activity typology for Visual Analytics, synthesizing a wide range of systems and activity concepts from the literature. Finally, we use this typology as the foundation of an activity-centered design process, highlighting both tensions and opportunities in the design space of VA systems.", "abstracts": [ { "abstractType": "Regular", "content": "As Visual Analytics (VA) research grows and diversifies to encompass new systems, techniques, and use contexts, gaining a holistic view of analytic practices is becoming ever more challenging. However, such a view is essential for researchers and practitioners seeking to develop systems for broad audiences that span multiple domains. In this paper, we interpret VA research through the lens of Activity Theory (AT)—a framework for modelling human activities that has been influential in the field of Human-Computer Interaction. We first provide an overview of Activity Theory, showing its potential for thinking beyond tasks, representations, and interactions to the broader systems of activity in which interactive tools are embedded and used. Next, we describe how Activity Theory can be used as an organizing framework in the construction of activity typologies, building and expanding upon the tradition of abstract task taxonomies in the field of Information Visualization. We then apply the resulting process to create an activity typology for Visual Analytics, synthesizing a wide range of systems and activity concepts from the literature. Finally, we use this typology as the foundation of an activity-centered design process, highlighting both tensions and opportunities in the design space of VA systems.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "As Visual Analytics (VA) research grows and diversifies to encompass new systems, techniques, and use contexts, gaining a holistic view of analytic practices is becoming ever more challenging. However, such a view is essential for researchers and practitioners seeking to develop systems for broad audiences that span multiple domains. In this paper, we interpret VA research through the lens of Activity Theory (AT)—a framework for modelling human activities that has been influential in the field of Human-Computer Interaction. We first provide an overview of Activity Theory, showing its potential for thinking beyond tasks, representations, and interactions to the broader systems of activity in which interactive tools are embedded and used. Next, we describe how Activity Theory can be used as an organizing framework in the construction of activity typologies, building and expanding upon the tradition of abstract task taxonomies in the field of Information Visualization. We then apply the resulting process to create an activity typology for Visual Analytics, synthesizing a wide range of systems and activity concepts from the literature. Finally, we use this typology as the foundation of an activity-centered design process, highlighting both tensions and opportunities in the design space of VA systems.", "title": "Beyond Tasks: An Activity Typology for Visual Analytics", "normalizedTitle": "Beyond Tasks: An Activity Typology for Visual Analytics", "fno": "08019880", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Activity Theory", "Visual Analytics", "Activity Centered Design", "Literature Review", "Human Computer Interaction" ], "authors": [ { "givenName": "Darren", "surname": "Edge", "fullName": "Darren Edge", "affiliation": "Microsoft Research", "__typename": "ArticleAuthorType" }, { "givenName": "Nathalie Henry", "surname": "Riche", "fullName": "Nathalie Henry Riche", "affiliation": "Microsoft Research", "__typename": "ArticleAuthorType" }, { "givenName": "Jonathan", "surname": "Larson", "fullName": "Jonathan Larson", "affiliation": "Microsoft Research", "__typename": "ArticleAuthorType" }, { "givenName": "Christopher", "surname": "White", "fullName": "Christopher White", "affiliation": "Microsoft Research", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "267-277", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/hicss/2016/5670/0/5670b226", "title": "A Purpose-Based Typology for Systemic Features Enabling Value Co-Creation in Consumer Information Systems", "doi": null, "abstractUrl": "/proceedings-article/hicss/2016/5670b226/12OmNwCJOY2", "parentPublication": { "id": "proceedings/hicss/2016/5670/0", "title": "2016 49th Hawaii International Conference on System Sciences (HICSS)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vast/2007/1659/0/04389028", "title": "From Tasks to Tools: A Field Study in Collaborative Visual Analytics", "doi": null, "abstractUrl": "/proceedings-article/vast/2007/04389028/12OmNxYL5gU", "parentPublication": { "id": "proceedings/vast/2007/1659/0", "title": "2007 IEEE Symposium on Visual Analytics Science and Technology", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "mags/cg/2015/02/mcg2015020016", "title": "Preparing Undergraduates for Visual Analytics", "doi": null, "abstractUrl": "/magazine/cg/2015/02/mcg2015020016/13rRUxjQyjN", "parentPublication": { "id": "mags/cg", "title": "IEEE Computer Graphics and Applications", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2013/12/ttg2013122376", "title": "A Multi-Level Typology of Abstract Visualization Tasks", "doi": null, "abstractUrl": "/journal/tg/2013/12/ttg2013122376/13rRUyYSWkX", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vast/2017/3163/0/08585498", "title": "The Role of Explicit Knowledge: A Conceptual Model of Knowledge-Assisted Visual Analytics", "doi": null, "abstractUrl": "/proceedings-article/vast/2017/08585498/17D45XvMccM", "parentPublication": { "id": "proceedings/vast/2017/3163/0", "title": "2017 IEEE Conference on Visual Analytics Science and Technology (VAST)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/fie/2018/1174/0/08659260", "title": "The WREASN Typology of Student Involvement Activities", "doi": null, "abstractUrl": "/proceedings-article/fie/2018/08659260/18j9bCxcE4U", "parentPublication": { "id": "proceedings/fie/2018/1174/0", "title": "2018 IEEE Frontiers in Education Conference (FIE)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2023/01/09906559", "title": "In Defence of Visual Analytics Systems: Replies to Critics", "doi": null, "abstractUrl": "/journal/tg/2023/01/09906559/1H5F2wJXT4Q", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/5555/01/09937145", "title": "The <italic>Transform-and-Perform</italic> framework: Explainable deep learning beyond classification", "doi": null, "abstractUrl": "/journal/tg/5555/01/09937145/1I05Bw9xb6o", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/trex/2020/8514/0/851400a009", "title": "Beyond Trust Building &#x2014; 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{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUxC0SWe", "doi": "10.1109/TVCG.2017.2743990", "abstract": "Data scientists and other analytic professionals often use interactive visualization in the dissemination phase at the end of a workflow during which findings are communicated to a wider audience. Visualization scientists, however, hold that interactive representation of data can also be used during exploratory analysis itself. Since the use of interactive visualization is optional rather than mandatory, this leaves a &#x201C;visualization gap&#x201D; during initial exploratory analysis that is the onus of visualization researchers to fill. In this paper, we explore areas where visualization would be beneficial in applied research by conducting a design study using a novel variation on contextual inquiry conducted with professional data analysts. Based on these interviews and experiments, we propose a set of interactive initial exploratory visualization guidelines which we believe will promote adoption by this type of user.", "abstracts": [ { "abstractType": "Regular", "content": "Data scientists and other analytic professionals often use interactive visualization in the dissemination phase at the end of a workflow during which findings are communicated to a wider audience. Visualization scientists, however, hold that interactive representation of data can also be used during exploratory analysis itself. Since the use of interactive visualization is optional rather than mandatory, this leaves a &#x201C;visualization gap&#x201D; during initial exploratory analysis that is the onus of visualization researchers to fill. In this paper, we explore areas where visualization would be beneficial in applied research by conducting a design study using a novel variation on contextual inquiry conducted with professional data analysts. Based on these interviews and experiments, we propose a set of interactive initial exploratory visualization guidelines which we believe will promote adoption by this type of user.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Data scientists and other analytic professionals often use interactive visualization in the dissemination phase at the end of a workflow during which findings are communicated to a wider audience. Visualization scientists, however, hold that interactive representation of data can also be used during exploratory analysis itself. Since the use of interactive visualization is optional rather than mandatory, this leaves a “visualization gap” during initial exploratory analysis that is the onus of visualization researchers to fill. In this paper, we explore areas where visualization would be beneficial in applied research by conducting a design study using a novel variation on contextual inquiry conducted with professional data analysts. Based on these interviews and experiments, we propose a set of interactive initial exploratory visualization guidelines which we believe will promote adoption by this type of user.", "title": "The Interactive Visualization Gap in Initial Exploratory Data Analysis", "normalizedTitle": "The Interactive Visualization Gap in Initial Exploratory Data Analysis", "fno": "08017577", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Data Analysis", "Data Visualisation", "Interactive Systems", "Interactive Visualization Gap", "Initial Exploratory Data Analysis", "Dissemination Phase", "Visualization Scientists", "Initial Exploratory Analysis", "Visualization Researchers", "Professional Data Analysts", "Interactive Initial Exploratory Visualization Guidelines", "Data Visualization", "Data Science", "Tools", "Visualization", "Big Data", "Interviews", "Data Science", "Visualization", "Visual Analytics", "Contextual Inquiry", "Semi Structured Interviews" ], "authors": [ { "givenName": "Andrea", "surname": "Batch", "fullName": "Andrea Batch", "affiliation": "College Park, University of Maryland, MD, USA", "__typename": "ArticleAuthorType" }, { "givenName": "Niklas", "surname": "Elmqvist", "fullName": "Niklas Elmqvist", "affiliation": "College Park, University of Maryland, MD, USA", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "278-287", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/big-data/2015/9926/0/07363993", "title": "Forecast UPC-level FMCG demand, Part I: Exploratory analysis and visualization", "doi": null, "abstractUrl": "/proceedings-article/big-data/2015/07363993/12OmNBtCCDh", "parentPublication": { "id": "proceedings/big-data/2015/9926/0", "title": "2015 IEEE International Conference on Big Data (Big Data)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/scc/2012/6218/0/06495851", "title": "Exploratory Climate Data Visualization and Analysis Using DV3D and UVCDAT", "doi": null, "abstractUrl": "/proceedings-article/scc/2012/06495851/12OmNqBbHWg", "parentPublication": { "id": "proceedings/scc/2012/6218/0", "title": "2012 SC Companion: High Performance Computing, Networking, Storage and Analysis (SCC)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/sccompanion/2012/4956/0/4956a483", "title": "Exploratory Climate Data Visualization and Analysis Using DV3D and UVCDAT", "doi": null, "abstractUrl": "/proceedings-article/sccompanion/2012/4956a483/12OmNwtn3BU", "parentPublication": { "id": "proceedings/sccompanion/2012/4956/0", "title": "2012 SC Companion: High Performance Computing, Networking Storage and Analysis", "__typename": "ParentPublication" }, 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{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUwwaKtd", "doi": "10.1109/TVCG.2017.2745078", "abstract": "People often rank and order data points as a vital part of making decisions. Multi-attribute ranking systems are a common tool used to make these data-driven decisions. Such systems often take the form of a table-based visualization in which users assign weights to the attributes representing the quantifiable importance of each attribute to a decision, which the system then uses to compute a ranking of the data. However, these systems assume that users are able to quantify their conceptual understanding of how important particular attributes are to a decision. This is not always easy or even possible for users to do. Rather, people often have a more holistic understanding of the data. They form opinions that data point A is better than data point B but do not necessarily know which attributes are important. To address these challenges, we present a visual analytic application to help people rank multi-variate data points. We developed a prototype system, Podium, that allows users to drag rows in the table to rank order data points based on their perception of the relative value of the data. Podium then infers a weighting model using Ranking SVM that satisfies the user's data preferences as closely as possible. Whereas past systems help users understand the relationships between data points based on changes to attribute weights, our approach helps users to understand the attributes that might inform their understanding of the data. We present two usage scenarios to describe some of the potential uses of our proposed technique: (1) understanding which attributes contribute to a user's subjective preferences for data, and (2) deconstructing attributes of importance for existing rankings. Our proposed approach makes powerful machine learning techniques more usable to those who may not have expertise in these areas.", "abstracts": [ { "abstractType": "Regular", "content": "People often rank and order data points as a vital part of making decisions. Multi-attribute ranking systems are a common tool used to make these data-driven decisions. Such systems often take the form of a table-based visualization in which users assign weights to the attributes representing the quantifiable importance of each attribute to a decision, which the system then uses to compute a ranking of the data. However, these systems assume that users are able to quantify their conceptual understanding of how important particular attributes are to a decision. This is not always easy or even possible for users to do. Rather, people often have a more holistic understanding of the data. They form opinions that data point A is better than data point B but do not necessarily know which attributes are important. To address these challenges, we present a visual analytic application to help people rank multi-variate data points. We developed a prototype system, Podium, that allows users to drag rows in the table to rank order data points based on their perception of the relative value of the data. Podium then infers a weighting model using Ranking SVM that satisfies the user's data preferences as closely as possible. Whereas past systems help users understand the relationships between data points based on changes to attribute weights, our approach helps users to understand the attributes that might inform their understanding of the data. We present two usage scenarios to describe some of the potential uses of our proposed technique: (1) understanding which attributes contribute to a user's subjective preferences for data, and (2) deconstructing attributes of importance for existing rankings. Our proposed approach makes powerful machine learning techniques more usable to those who may not have expertise in these areas.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "People often rank and order data points as a vital part of making decisions. Multi-attribute ranking systems are a common tool used to make these data-driven decisions. Such systems often take the form of a table-based visualization in which users assign weights to the attributes representing the quantifiable importance of each attribute to a decision, which the system then uses to compute a ranking of the data. However, these systems assume that users are able to quantify their conceptual understanding of how important particular attributes are to a decision. This is not always easy or even possible for users to do. Rather, people often have a more holistic understanding of the data. They form opinions that data point A is better than data point B but do not necessarily know which attributes are important. To address these challenges, we present a visual analytic application to help people rank multi-variate data points. We developed a prototype system, Podium, that allows users to drag rows in the table to rank order data points based on their perception of the relative value of the data. Podium then infers a weighting model using Ranking SVM that satisfies the user's data preferences as closely as possible. Whereas past systems help users understand the relationships between data points based on changes to attribute weights, our approach helps users to understand the attributes that might inform their understanding of the data. We present two usage scenarios to describe some of the potential uses of our proposed technique: (1) understanding which attributes contribute to a user's subjective preferences for data, and (2) deconstructing attributes of importance for existing rankings. Our proposed approach makes powerful machine learning techniques more usable to those who may not have expertise in these areas.", "title": "Podium: Ranking Data Using Mixed-Initiative Visual Analytics", "normalizedTitle": "Podium: Ranking Data Using Mixed-Initiative Visual Analytics", "fno": "08019863", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Data Visualization", "Support Vector Machines", "Visual Analytics", "Data Models", "Prototypes", "Computational Modeling", "Mixed Initiative Visual Analytics", "Multi Attribute Ranking", "User Interaction" ], "authors": [ { "givenName": "Emily", "surname": "Wall", "fullName": "Emily Wall", "affiliation": "Georgia Institute of Technology, Atlanta, GA, USA", "__typename": "ArticleAuthorType" }, { "givenName": "Subhajit", "surname": "Das", "fullName": "Subhajit Das", "affiliation": "Georgia Institute of Technology, Atlanta, GA, USA", "__typename": "ArticleAuthorType" }, { "givenName": "Ravish", "surname": "Chawla", "fullName": "Ravish Chawla", "affiliation": "Georgia Institute of Technology, Atlanta, GA, USA", "__typename": "ArticleAuthorType" }, { "givenName": "Bharath", "surname": "Kalidindi", "fullName": "Bharath Kalidindi", "affiliation": "Georgia Institute of Technology, Atlanta, GA, USA", "__typename": "ArticleAuthorType" }, { "givenName": "Eli T.", "surname": "Brown", "fullName": "Eli T. Brown", "affiliation": "DePaul University, Chicago, IL, USA", "__typename": "ArticleAuthorType" }, { "givenName": "Alex", "surname": "Endert", "fullName": "Alex Endert", "affiliation": "Georgia Institute of Technology, Atlanta, GA, USA", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "288-297", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/icdmw/2010/4257/0/4257a388", "title": "A Visual Analytics Tool for Analysing Microarray Data", "doi": null, "abstractUrl": "/proceedings-article/icdmw/2010/4257a388/12OmNvlg8nK", "parentPublication": { "id": "proceedings/icdmw/2010/4257/0", "title": "2010 IEEE International Conference on Data Mining Workshops", "__typename": "ParentPublication" }, "__typename": 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Augmentation Using Knowledge Graphs", "doi": null, "abstractUrl": "/journal/tg/2021/02/09222249/1nTroT3Yn72", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vis/2021/3335/0/333500a121", "title": "A Mixed-Initiative Visual Analytics Approach for Qualitative Causal Modeling", "doi": null, "abstractUrl": "/proceedings-article/vis/2021/333500a121/1yXubl1hwk0", "parentPublication": { "id": "proceedings/vis/2021/3335/0", "title": "2021 IEEE Visualization Conference (VIS)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "08017577", "articleId": "13rRUxC0SWe", "__typename": "AdjacentArticleType" }, "next": { "fno": "08019851", "articleId": "13rRUxBrGh7", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [ { "id": 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{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUxBrGh7", "doi": "10.1109/TVCG.2017.2744818", "abstract": "Labeling data instances is an important task in machine learning and visual analytics. Both fields provide a broad set of labeling strategies, whereby machine learning (and in particular active learning) follows a rather model-centered approach and visual analytics employs rather user-centered approaches (visual-interactive labeling). Both approaches have individual strengths and weaknesses. In this work, we conduct an experiment with three parts to assess and compare the performance of these different labeling strategies. In our study, we (1) identify different visual labeling strategies for user-centered labeling, (2) investigate strengths and weaknesses of labeling strategies for different labeling tasks and task complexities, and (3) shed light on the effect of using different visual encodings to guide the visual-interactive labeling process. We further compare labeling of single versus multiple instances at a time, and quantify the impact on efficiency. We systematically compare the performance of visual interactive labeling with that of active learning. Our main findings are that visual-interactive labeling can outperform active learning, given the condition that dimension reduction separates well the class distributions. Moreover, using dimension reduction in combination with additional visual encodings that expose the internal state of the learning model turns out to improve the performance of visual-interactive labeling.", "abstracts": [ { "abstractType": "Regular", "content": "Labeling data instances is an important task in machine learning and visual analytics. Both fields provide a broad set of labeling strategies, whereby machine learning (and in particular active learning) follows a rather model-centered approach and visual analytics employs rather user-centered approaches (visual-interactive labeling). Both approaches have individual strengths and weaknesses. In this work, we conduct an experiment with three parts to assess and compare the performance of these different labeling strategies. In our study, we (1) identify different visual labeling strategies for user-centered labeling, (2) investigate strengths and weaknesses of labeling strategies for different labeling tasks and task complexities, and (3) shed light on the effect of using different visual encodings to guide the visual-interactive labeling process. We further compare labeling of single versus multiple instances at a time, and quantify the impact on efficiency. We systematically compare the performance of visual interactive labeling with that of active learning. Our main findings are that visual-interactive labeling can outperform active learning, given the condition that dimension reduction separates well the class distributions. Moreover, using dimension reduction in combination with additional visual encodings that expose the internal state of the learning model turns out to improve the performance of visual-interactive labeling.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Labeling data instances is an important task in machine learning and visual analytics. Both fields provide a broad set of labeling strategies, whereby machine learning (and in particular active learning) follows a rather model-centered approach and visual analytics employs rather user-centered approaches (visual-interactive labeling). Both approaches have individual strengths and weaknesses. In this work, we conduct an experiment with three parts to assess and compare the performance of these different labeling strategies. In our study, we (1) identify different visual labeling strategies for user-centered labeling, (2) investigate strengths and weaknesses of labeling strategies for different labeling tasks and task complexities, and (3) shed light on the effect of using different visual encodings to guide the visual-interactive labeling process. We further compare labeling of single versus multiple instances at a time, and quantify the impact on efficiency. We systematically compare the performance of visual interactive labeling with that of active learning. Our main findings are that visual-interactive labeling can outperform active learning, given the condition that dimension reduction separates well the class distributions. Moreover, using dimension reduction in combination with additional visual encodings that expose the internal state of the learning model turns out to improve the performance of visual-interactive labeling.", "title": "Comparing Visual-Interactive Labeling with Active Learning: An Experimental Study", "normalizedTitle": "Comparing Visual-Interactive Labeling with Active Learning: An Experimental Study", "fno": "08019851", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Labeling", "Visual Analytics", "Data Models", "Uncertainty", "Data Visualization", "Labeling", "Visual Interactive Labeling", "Information Visualization", "Visual Analytics", "Active Learning", "Machine Learning", "Classification", "Evaluation", "Experiment", "Dimensionality Reduction" ], "authors": [ { "givenName": "Jürgen", "surname": "Bernard", "fullName": "Jürgen Bernard", "affiliation": "Technische Universität Darmstadt, Darmstadt, Germany", "__typename": "ArticleAuthorType" }, { "givenName": "Marco", "surname": "Hutter", "fullName": "Marco Hutter", "affiliation": "Technische Universität Darmstadt, Darmstadt, Germany", "__typename": "ArticleAuthorType" }, { "givenName": "Matthias", "surname": "Zeppelzauer", "fullName": "Matthias Zeppelzauer", "affiliation": "St. Pölten University of Applied Sciences, St. Pölten, Austria", "__typename": "ArticleAuthorType" }, { "givenName": "Dieter", "surname": "Fellner", "fullName": "Dieter Fellner", "affiliation": "Fraunhofer IGD, Darmstadt, Germany", "__typename": "ArticleAuthorType" }, { "givenName": "Michael", "surname": "Sedlmair", "fullName": "Michael Sedlmair", "affiliation": "University of Vienna, Vienna, Austria", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "298-308", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" 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asynchronous labeling", "doi": null, "abstractUrl": "/proceedings-article/big-data/2015/07363766/12OmNyoSb9g", "parentPublication": { "id": "proceedings/big-data/2015/9926/0", "title": "2015 IEEE International Conference on Big Data (Big Data)", "__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/2017/01/07539297", "title": "Visual Analytics for Mobile Eye Tracking", "doi": null, "abstractUrl": "/journal/tg/2017/01/07539297/13rRUyv53Fx", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2023/01/09904017", "title": "Visual Concept Programming: A Visual Analytics Approach to Injecting Human Intelligence at Scale", "doi": null, "abstractUrl": "/journal/tg/2023/01/09904017/1H0GlgwfKak", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2020/01/08805463", "title": "VASSL: A Visual Analytics Toolkit for Social Spambot Labeling", "doi": null, "abstractUrl": "/journal/tg/2020/01/08805463/1cG4JtVNK2A", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/big-data/2019/0858/0/09006224", "title": "Active Learning Strategies for Hierarchical Labeling Microtasks", "doi": null, "abstractUrl": "/proceedings-article/big-data/2019/09006224/1hJsmY3hhte", "parentPublication": { "id": "proceedings/big-data/2019/0858/0", "title": "2019 IEEE International Conference on Big Data (Big Data)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iv/2021/3827/0/382700a211", "title": "Visual Analytics and Similarity Search - Interest-based Similarity Search in Scientific Data", "doi": null, "abstractUrl": "/proceedings-article/iv/2021/382700a211/1y4oJ30dpcY", "parentPublication": { "id": "proceedings/iv/2021/3827/0", "title": "2021 25th International Conference Information Visualisation (IV)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/ispa-bdcloud-socialcom-sustaincom/2021/3574/0/357400a019", "title": "SLAMVis: An Interactive Visualization Approach for Smart Labeling on Multidimensional Data", "doi": null, "abstractUrl": "/proceedings-article/ispa-bdcloud-socialcom-sustaincom/2021/357400a019/1zxKYRTw9Fu", "parentPublication": { "id": "proceedings/ispa-bdcloud-socialcom-sustaincom/2021/3574/0", "title": "2021 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "08019863", "articleId": "13rRUwwaKtd", "__typename": "AdjacentArticleType" }, "next": { "fno": "08019833", "articleId": "13rRUNvgz9X", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [ { "id": "17ShDTXWRMI", "name": "ttg201801-08019851s1.zip", "location": "https://www.computer.org/csdl/api/v1/extra/ttg201801-08019851s1.zip", "extension": "zip", "size": "8.74 MB", "__typename": "WebExtraType" } ], "articleVideos": [] }
{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUNvgz9X", "doi": "10.1109/TVCG.2017.2744684", "abstract": "Interactive visual data analysis is most productive when users can focus on answering the questions they have about their data, rather than focusing on how to operate the interface to the analysis tool. One viable approach to engaging users in interactive conversations with their data is a natural language interface to visualizations. These interfaces have the potential to be both more expressive and more accessible than other interaction paradigms. We explore how principles from language pragmatics can be applied to the flow of visual analytical conversations, using natural language as an input modality. We evaluate the effectiveness of pragmatics support in our system Evizeon, and present design considerations for conversation interfaces to visual analytics tools.", "abstracts": [ { "abstractType": "Regular", "content": "Interactive visual data analysis is most productive when users can focus on answering the questions they have about their data, rather than focusing on how to operate the interface to the analysis tool. One viable approach to engaging users in interactive conversations with their data is a natural language interface to visualizations. These interfaces have the potential to be both more expressive and more accessible than other interaction paradigms. We explore how principles from language pragmatics can be applied to the flow of visual analytical conversations, using natural language as an input modality. We evaluate the effectiveness of pragmatics support in our system Evizeon, and present design considerations for conversation interfaces to visual analytics tools.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Interactive visual data analysis is most productive when users can focus on answering the questions they have about their data, rather than focusing on how to operate the interface to the analysis tool. One viable approach to engaging users in interactive conversations with their data is a natural language interface to visualizations. These interfaces have the potential to be both more expressive and more accessible than other interaction paradigms. We explore how principles from language pragmatics can be applied to the flow of visual analytical conversations, using natural language as an input modality. We evaluate the effectiveness of pragmatics support in our system Evizeon, and present design considerations for conversation interfaces to visual analytics tools.", "title": "Applying Pragmatics Principles for Interaction with Visual Analytics", "normalizedTitle": "Applying Pragmatics Principles for Interaction with Visual Analytics", "fno": "08019833", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Pragmatics", "Visual Analytics", "Natural Languages", "Data Visualization", "Coherence", "Tools", "Natural Language", "Interaction", "Language Pragmatics", "Visual Analytics", "Ambiguity", "Feedback" ], "authors": [ { "givenName": "Enamul", "surname": "Hoque", "fullName": "Enamul Hoque", "affiliation": "Stanford University", "__typename": "ArticleAuthorType" }, { "givenName": "Vidya", "surname": "Setlur", "fullName": "Vidya Setlur", "affiliation": "Tableau Research", "__typename": "ArticleAuthorType" }, { "givenName": "Melanie", "surname": "Tory", "fullName": "Melanie Tory", "affiliation": "Tableau Research", "__typename": "ArticleAuthorType" }, { "givenName": "Isaac", "surname": "Dykeman", "fullName": "Isaac Dykeman", "affiliation": "Rice University", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": false, "showRecommendedArticles": true, "isOpenAccess": true, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "309-318", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/hicss/2013/4892/0/4892b495", "title": "A Role for Reasoning in Visual Analytics", "doi": null, "abstractUrl": "/proceedings-article/hicss/2013/4892b495/12OmNqJ8tq4", "parentPublication": { "id": "proceedings/hicss/2013/4892/0", "title": "2013 46th Hawaii International Conference on System Sciences", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": 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Analytics", "doi": null, "abstractUrl": "/proceedings-article/hicss/2011/05718615/12OmNxGSm6x", "parentPublication": { "id": "proceedings/hicss/2011/9618/0", "title": "2011 44th Hawaii International Conference on System Sciences", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/percomw/2016/1941/0/07457127", "title": "Integrating quality of information with pragmatic assistance", "doi": null, "abstractUrl": "/proceedings-article/percomw/2016/07457127/12OmNxecS2l", "parentPublication": { "id": "proceedings/percomw/2016/1941/0", "title": "2016 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vast/2014/6227/0/07042508", "title": "Emoticons and linguistic alignment: How visual analytics can elicit storytelling", "doi": null, "abstractUrl": "/proceedings-article/vast/2014/07042508/12OmNxzMnLL", "parentPublication": { "id": "proceedings/vast/2014/6227/0", "title": "2014 IEEE Conference on Visual Analytics Science and Technology (VAST)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vis/2022/8812/0/881200a006", "title": "Facilitating Conversational Interaction in Natural Language Interfaces for Visualization", "doi": null, "abstractUrl": "/proceedings-article/vis/2022/881200a006/1J6hcTVtKNy", "parentPublication": { "id": "proceedings/vis/2022/8812/0", "title": "2022 IEEE Visualization and Visual Analytics (VIS)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/chase/2019/2239/0/223900a079", "title": "Pragmatic Characteristics of Security Conversations: An Exploratory Linguistic Analysis", "doi": null, "abstractUrl": "/proceedings-article/chase/2019/223900a079/1cTIDQJkWaY", "parentPublication": { "id": 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Visualization Conference (VIS)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "08019851", "articleId": "13rRUxBrGh7", "__typename": "AdjacentArticleType" }, "next": { "fno": "08017652", "articleId": "13rRUwgQpDy", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [ { "id": "17ShDTXWREZ", "name": "ttg201801-08019833s1.zip", "location": "https://www.computer.org/csdl/api/v1/extra/ttg201801-08019833s1.zip", "extension": "zip", "size": "11 MB", "__typename": "WebExtraType" } ], "articleVideos": [] }
{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUwgQpDy", "doi": "10.1109/TVCG.2017.2744418", "abstract": "The fields of operations research and computer science have long sought to find automatic solver techniques that can find high-quality solutions to difficult real-world optimisation problems. The traditional workflow is to exactly model the problem and then enter this model into a general-purpose &#x201C;black-box&#x201D; solver. In practice, however, many problems cannot be solved completely automatically, but require a &#x201C;human-in-the-loop&#x201D; to iteratively refine the model and give hints to the solver. In this paper, we explore the parallels between this interactive optimisation workflow and the visual analytics sense-making loop. We assert that interactive optimisation is essentially a visual analytics task and propose a problem-solving loop analogous to the sense-making loop. We explore these ideas through an in-depth analysis of a use-case in prostate brachytherapy, an application where interactive optimisation may be able to provide significant assistance to practitioners in creating prostate cancer treatment plans customised to each patient's tumour characteristics. However, current brachytherapy treatment planning is usually a careful, mostly manual process involving multiple professionals. We developed a prototype interactive optimisation tool for brachytherapy that goes beyond current practice in supporting focal therapy - targeting tumour cells directly rather than simply seeking coverage of the whole prostate gland. We conducted semi-structured interviews, in two stages, with seven radiation oncology professionals in order to establish whether they would prefer to use interactive optimisation for treatment planning and whether such a tool could improve their trust in the novel focal therapy approach and in machine generated solutions to the problem.", "abstracts": [ { "abstractType": "Regular", "content": "The fields of operations research and computer science have long sought to find automatic solver techniques that can find high-quality solutions to difficult real-world optimisation problems. The traditional workflow is to exactly model the problem and then enter this model into a general-purpose &#x201C;black-box&#x201D; solver. In practice, however, many problems cannot be solved completely automatically, but require a &#x201C;human-in-the-loop&#x201D; to iteratively refine the model and give hints to the solver. In this paper, we explore the parallels between this interactive optimisation workflow and the visual analytics sense-making loop. We assert that interactive optimisation is essentially a visual analytics task and propose a problem-solving loop analogous to the sense-making loop. We explore these ideas through an in-depth analysis of a use-case in prostate brachytherapy, an application where interactive optimisation may be able to provide significant assistance to practitioners in creating prostate cancer treatment plans customised to each patient's tumour characteristics. However, current brachytherapy treatment planning is usually a careful, mostly manual process involving multiple professionals. We developed a prototype interactive optimisation tool for brachytherapy that goes beyond current practice in supporting focal therapy - targeting tumour cells directly rather than simply seeking coverage of the whole prostate gland. We conducted semi-structured interviews, in two stages, with seven radiation oncology professionals in order to establish whether they would prefer to use interactive optimisation for treatment planning and whether such a tool could improve their trust in the novel focal therapy approach and in machine generated solutions to the problem.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "The fields of operations research and computer science have long sought to find automatic solver techniques that can find high-quality solutions to difficult real-world optimisation problems. The traditional workflow is to exactly model the problem and then enter this model into a general-purpose “black-box” solver. In practice, however, many problems cannot be solved completely automatically, but require a “human-in-the-loop” to iteratively refine the model and give hints to the solver. In this paper, we explore the parallels between this interactive optimisation workflow and the visual analytics sense-making loop. We assert that interactive optimisation is essentially a visual analytics task and propose a problem-solving loop analogous to the sense-making loop. We explore these ideas through an in-depth analysis of a use-case in prostate brachytherapy, an application where interactive optimisation may be able to provide significant assistance to practitioners in creating prostate cancer treatment plans customised to each patient's tumour characteristics. However, current brachytherapy treatment planning is usually a careful, mostly manual process involving multiple professionals. We developed a prototype interactive optimisation tool for brachytherapy that goes beyond current practice in supporting focal therapy - targeting tumour cells directly rather than simply seeking coverage of the whole prostate gland. We conducted semi-structured interviews, in two stages, with seven radiation oncology professionals in order to establish whether they would prefer to use interactive optimisation for treatment planning and whether such a tool could improve their trust in the novel focal therapy approach and in machine generated solutions to the problem.", "title": "Understanding the Relationship Between Interactive Optimisation and Visual Analytics in the Context of Prostate Brachytherapy", "normalizedTitle": "Understanding the Relationship Between Interactive Optimisation and Visual Analytics in the Context of Prostate Brachytherapy", "fno": "08017652", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Biological Organs", "Brachytherapy", "Cancer", "Cellular Biophysics", "Interactive Systems", "Medical Computing", "Tumours", "Prostate Brachytherapy", "Operations Research", "Computer Science", "Automatic Solver Techniques", "Human In The Loop", "Interactive Optimisation Workflow", "Visual Analytics Sense Making Loop", "Problem Solving Loop Analogous", "Prototype Interactive Optimisation Tool", "Prostate Cancer Treatment Plans", "Brachytherapy Treatment Planning", "Black Box Solver", "Sense Making Loop", "In Depth Analysis", "Tumour Cells", "Optimization", "Tools", "Visual Analytics", "Mathematical Model", "Brachytherapy", "Planning", "Visual Analytics", "Interactive Optimisation", "Interactive Systems And Tools", "Prostate Brachytherapy" ], "authors": [ { "givenName": "Jie", "surname": "Liu", "fullName": "Jie Liu", "affiliation": "Monash University and Data61", "__typename": "ArticleAuthorType" }, { "givenName": "Tim", "surname": "Dwyer", "fullName": "Tim Dwyer", "affiliation": "Monash University", "__typename": "ArticleAuthorType" }, { "givenName": "Kim", "surname": "Marriott", "fullName": "Kim Marriott", "affiliation": "Monash University and Data61", "__typename": "ArticleAuthorType" }, { "givenName": "Jeremy", "surname": "Millar", "fullName": "Jeremy Millar", "affiliation": "Monash University and Alfred Health", "__typename": "ArticleAuthorType" }, { "givenName": "Annette", "surname": "Haworth", "fullName": "Annette Haworth", "affiliation": "University of Sydney", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "319-329", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/dfma/2005/2273/0/22730303", "title": "Real-Time Treatment Planning Optimisation for Brachytherapy", "doi": null, "abstractUrl": "/proceedings-article/dfma/2005/22730303/12OmNwDSdII", "parentPublication": { "id": "proceedings/dfma/2005/2273/0", "title": "Proceedings. 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First International Conference on Distributed Frameworks for Multimedia Applications", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/haptics/2010/6821/0/05444612", "title": "Haptic system design for MRI-guided needle based prostate brachytherapy", "doi": null, "abstractUrl": "/proceedings-article/haptics/2010/05444612/12OmNyQYttN", "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/bibe/2010/4083/0/4083a203", "title": "Modular Software Design for Brachytherapy Image-Guided Robotic Systems", "doi": null, "abstractUrl": "/proceedings-article/bibe/2010/4083a203/12OmNzlD9DT", "parentPublication": { "id": "proceedings/bibe/2010/4083/0", "title": "2010 IEEE International Conference on Bioinformatics and Bioengineering", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/case/2012/0430/0/06386483", "title": "Initial experiments toward automated robotic implantation of skew-line needle arrangements for HDR brachytherapy", "doi": null, "abstractUrl": "/proceedings-article/case/2012/06386483/12OmNzy7uQS", "parentPublication": { "id": "proceedings/case/2012/0430/0", "title": "2012 IEEE International Conference on Automation Science and Engineering (CASE 2012)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/th/2011/03/tth2011030188", "title": "Haptic Simulator for Prostate Brachytherapy with Simulated Needle and Probe Interaction", "doi": null, "abstractUrl": "/journal/th/2011/03/tth2011030188/13rRUILtJr3", "parentPublication": { "id": "trans/th", "title": "IEEE Transactions on Haptics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2018/01/08019833", "title": "Applying Pragmatics Principles for Interaction with Visual Analytics", "doi": null, "abstractUrl": "/journal/tg/2018/01/08019833/13rRUNvgz9X", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/bibm/2022/6819/0/09995677", "title": "Explainability-guided Mathematical Model-Based Segmentation of Transrectal Ultrasound Images for Prostate Brachytherapy", "doi": null, "abstractUrl": "/proceedings-article/bibm/2022/09995677/1JC2XzbSjhS", "parentPublication": { "id": "proceedings/bibm/2022/6819/0", "title": "2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vizsec/2019/3876/0/09161563", "title": "A Visual Analytics Framework for Adversarial Text Generation", "doi": null, "abstractUrl": "/proceedings-article/vizsec/2019/09161563/1m6hHu2C1LG", "parentPublication": { "id": "proceedings/vizsec/2019/3876/0", "title": "2019 IEEE Symposium on Visualization for Cyber Security (VizSec)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2021/02/09241744", "title": "Supporting the Problem-Solving Loop: Designing Highly Interactive Optimisation Systems", "doi": null, "abstractUrl": "/journal/tg/2021/02/09241744/1oijOjuyCNq", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vahc/2020/2644/0/264400a017", "title": "Visualization Co-Design with Prostate Cancer Survivors who have Limited Graph Literacy", "doi": null, "abstractUrl": "/proceedings-article/vahc/2020/264400a017/1yhFE7okzgk", "parentPublication": { "id": "proceedings/vahc/2020/2644/0", "title": "2020 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{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUxNEqQ0", "doi": "10.1109/TVCG.2017.2744758", "abstract": "Financial institutions are interested in ensuring security and quality for their customers. Banks, for instance, need to identify and stop harmful transactions in a timely manner. In order to detect fraudulent operations, data mining techniques and customer profile analysis are commonly used. However, these approaches are not supported by Visual Analytics techniques yet. Visual Analytics techniques have potential to considerably enhance the knowledge discovery process and increase the detection and prediction accuracy of financial fraud detection systems. Thus, we propose EVA, a Visual Analytics approach for supporting fraud investigation, fine-tuning fraud detection algorithms, and thus, reducing false positive alarms.", "abstracts": [ { "abstractType": "Regular", "content": "Financial institutions are interested in ensuring security and quality for their customers. Banks, for instance, need to identify and stop harmful transactions in a timely manner. In order to detect fraudulent operations, data mining techniques and customer profile analysis are commonly used. However, these approaches are not supported by Visual Analytics techniques yet. Visual Analytics techniques have potential to considerably enhance the knowledge discovery process and increase the detection and prediction accuracy of financial fraud detection systems. Thus, we propose EVA, a Visual Analytics approach for supporting fraud investigation, fine-tuning fraud detection algorithms, and thus, reducing false positive alarms.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Financial institutions are interested in ensuring security and quality for their customers. Banks, for instance, need to identify and stop harmful transactions in a timely manner. In order to detect fraudulent operations, data mining techniques and customer profile analysis are commonly used. However, these approaches are not supported by Visual Analytics techniques yet. Visual Analytics techniques have potential to considerably enhance the knowledge discovery process and increase the detection and prediction accuracy of financial fraud detection systems. Thus, we propose EVA, a Visual Analytics approach for supporting fraud investigation, fine-tuning fraud detection algorithms, and thus, reducing false positive alarms.", "title": "EVA: Visual Analytics to Identify Fraudulent Events", "normalizedTitle": "EVA: Visual Analytics to Identify Fraudulent Events", "fno": "08023780", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Data Visualization", "Complexity Theory", "Visual Analytics", "Data Mining", "Event Detection", "Visual Knowledge Discovery", "Time Series Data", "Business And Finance Visualization", "Financial Fraud Detection" ], "authors": [ { "givenName": "Roger A.", "surname": "Leite", "fullName": "Roger A. Leite", "affiliation": "Vienna University of Technology", "__typename": "ArticleAuthorType" }, { "givenName": "Theresia", "surname": "Gschwandtner", "fullName": "Theresia Gschwandtner", "affiliation": "Vienna University of Technology", "__typename": "ArticleAuthorType" }, { "givenName": "Silvia", "surname": "Miksch", "fullName": "Silvia Miksch", "affiliation": "Vienna University of Technology", "__typename": "ArticleAuthorType" }, { "givenName": "Simone", "surname": "Kriglstein", "fullName": "Simone Kriglstein", "affiliation": "Faculty of Computer Science, University of Vienna, Austria", "__typename": "ArticleAuthorType" }, { "givenName": "Margit", "surname": "Pohl", "fullName": "Margit Pohl", "affiliation": "Vienna University of Technology", "__typename": "ArticleAuthorType" }, { "givenName": "Erich", "surname": "Gstrein", "fullName": "Erich Gstrein", "affiliation": "Erste Group IT International, Austria", "__typename": "ArticleAuthorType" }, { "givenName": "Johannes", "surname": "Kuntner", "fullName": "Johannes Kuntner", "affiliation": "Erste Group IT International, Austria", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "330-339", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/iv/2010/7846/0/05571363", "title": "Extracting Events from Spatial Time Series", "doi": null, "abstractUrl": "/proceedings-article/iv/2010/05571363/12OmNA1mbcE", "parentPublication": { "id": "proceedings/iv/2010/7846/0", "title": "2010 14th International Conference Information Visualisation", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vizsec/2015/7599/0/07312770", "title": "Discovery of rating fraud with real-time streaming visual analytics", "doi": null, "abstractUrl": "/proceedings-article/vizsec/2015/07312770/12OmNAGepXg", "parentPublication": { "id": "proceedings/vizsec/2015/7599/0", "title": "2015 IEEE Symposium on Visualization for Cyber Security (VizSec)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/pacificvis/2018/1424/0/142401a160", "title": "Visual Analytics for Networked-Guarantee Loans Risk Management", "doi": null, "abstractUrl": "/proceedings-article/pacificvis/2018/142401a160/12OmNBpVPS1", "parentPublication": { "id": "proceedings/pacificvis/2018/1424/0", "title": "2018 IEEE Pacific Visualization Symposium (PacificVis)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vast/2012/4752/0/06400514", "title": "Big data exploration through visual analytics", "doi": null, "abstractUrl": "/proceedings-article/vast/2012/06400514/12OmNC3XhwY", "parentPublication": { "id": "proceedings/vast/2012/4752/0", "title": "2012 IEEE Conference on Visual Analytics Science and Technology (VAST 2012)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vast/2015/9783/0/07347678", "title": "Visual Analytics for fraud detection and monitoring", "doi": null, "abstractUrl": "/proceedings-article/vast/2015/07347678/12OmNCxtyJT", "parentPublication": { "id": "proceedings/vast/2015/9783/0", "title": "2015 IEEE Conference on Visual Analytics Science and Technology (VAST)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iv/2009/3733/0/3733a197", "title": "A Visualization Approach for Frauds Detection in Financial Market", "doi": null, "abstractUrl": "/proceedings-article/iv/2009/3733a197/12OmNvnOwqz", "parentPublication": { "id": "proceedings/iv/2009/3733/0", "title": "2009 13th International Conference Information Visualisation", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "mags/co/2013/08/mco2013080090", "title": "Bixplorer: Visual Analytics with Biclusters", "doi": null, "abstractUrl": "/magazine/co/2013/08/mco2013080090/13rRUwcAqvs", "parentPublication": { "id": "mags/co", "title": "Computer", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "mags/cg/2009/02/mcg2009020084", "title": "Demystifying Visual Analytics", "doi": null, "abstractUrl": "/magazine/cg/2009/02/mcg2009020084/13rRUy3gn3z", "parentPublication": { "id": "mags/cg", "title": "IEEE Computer Graphics and Applications", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/5555/01/10081495", "title": "FraudAuditor: A Visual Analytics Approach for Collusive Fraud in Health Insurance", "doi": null, "abstractUrl": "/journal/tg/5555/01/10081495/1LRbQCd2D7O", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": 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{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUytWF9s", "doi": "10.1109/TVCG.2017.2745279", "abstract": "During asynchronous collaborative analysis, handoff of partial findings is challenging because externalizations produced by analysts may not adequately communicate their investigative process. To address this challenge, we developed techniques to automatically capture and help encode tacit aspects of the investigative process based on an analyst's interactions, and streamline explicit authoring of handoff annotations. We designed our techniques to mediate awareness of analysis coverage, support explicit communication of progress and uncertainty with annotation, and implicit communication through playback of investigation histories. To evaluate our techniques, we developed an interactive visual analysis system, KTGraph, that supports an asynchronous investigative document analysis task. We conducted a two-phase user study to characterize a set of handoff strategies and to compare investigative performance with and without our techniques. The results suggest that our techniques promote the use of more effective handoff strategies, help increase an awareness of prior investigative process and insights, as well as improve final investigative outcomes.", "abstracts": [ { "abstractType": "Regular", "content": "During asynchronous collaborative analysis, handoff of partial findings is challenging because externalizations produced by analysts may not adequately communicate their investigative process. To address this challenge, we developed techniques to automatically capture and help encode tacit aspects of the investigative process based on an analyst's interactions, and streamline explicit authoring of handoff annotations. We designed our techniques to mediate awareness of analysis coverage, support explicit communication of progress and uncertainty with annotation, and implicit communication through playback of investigation histories. To evaluate our techniques, we developed an interactive visual analysis system, KTGraph, that supports an asynchronous investigative document analysis task. We conducted a two-phase user study to characterize a set of handoff strategies and to compare investigative performance with and without our techniques. The results suggest that our techniques promote the use of more effective handoff strategies, help increase an awareness of prior investigative process and insights, as well as improve final investigative outcomes.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "During asynchronous collaborative analysis, handoff of partial findings is challenging because externalizations produced by analysts may not adequately communicate their investigative process. To address this challenge, we developed techniques to automatically capture and help encode tacit aspects of the investigative process based on an analyst's interactions, and streamline explicit authoring of handoff annotations. We designed our techniques to mediate awareness of analysis coverage, support explicit communication of progress and uncertainty with annotation, and implicit communication through playback of investigation histories. To evaluate our techniques, we developed an interactive visual analysis system, KTGraph, that supports an asynchronous investigative document analysis task. We conducted a two-phase user study to characterize a set of handoff strategies and to compare investigative performance with and without our techniques. The results suggest that our techniques promote the use of more effective handoff strategies, help increase an awareness of prior investigative process and insights, as well as improve final investigative outcomes.", "title": "Supporting Handoff in Asynchronous Collaborative Sensemaking Using Knowledge-Transfer Graphs", "normalizedTitle": "Supporting Handoff in Asynchronous Collaborative Sensemaking Using Knowledge-Transfer Graphs", "fno": "08017596", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Collaboration", "Visual Analytics", "Data Analysis", "Data Visualization", "History", "Tools", "Collaboration", "Sensemaking", "Handoff", "Handover", "Structured Externalizations", "Interactive Visual Analysis" ], "authors": [ { "givenName": "Jian", "surname": "Zhao", "fullName": "Jian Zhao", "affiliation": "FX Palo Alto Laboratory", "__typename": "ArticleAuthorType" }, { "givenName": "Michael", "surname": "Glueck", "fullName": "Michael Glueck", "affiliation": "Autodesk Research", "__typename": "ArticleAuthorType" }, { "givenName": "Petra", "surname": "Isenberg", "fullName": "Petra Isenberg", "affiliation": "Inria", "__typename": "ArticleAuthorType" }, { "givenName": "Fanny", "surname": "Chevalier", "fullName": "Fanny Chevalier", "affiliation": "Inria", "__typename": "ArticleAuthorType" }, { "givenName": "Azam", "surname": "Khan", "fullName": "Azam Khan", "affiliation": "Autodesk Research", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "340-350", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/hicss/2013/4892/0/4892c416", "title": "Visual Analytics for Public Health: Supporting Knowledge Construction and Decision-Making", "doi": null, "abstractUrl": "/proceedings-article/hicss/2013/4892c416/12OmNrJiCNq", "parentPublication": { "id": "proceedings/hicss/2013/4892/0", "title": "2013 46th Hawaii International Conference on System Sciences", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iv/2014/4103/0/4103a225", "title": "SchemaLine: Timeline Visualization for Sensemaking", "doi": null, "abstractUrl": "/proceedings-article/iv/2014/4103a225/12OmNvjQ92N", "parentPublication": { "id": "proceedings/iv/2014/4103/0", "title": "2014 18th International Conference on Information Visualisation (IV)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vast/2012/4752/0/06400558", "title": "SocialNetSense: Supporting sensemaking of social and structural features in networks with interactive visualization", "doi": null, "abstractUrl": "/proceedings-article/vast/2012/06400558/12OmNxdm4ya", "parentPublication": { "id": "proceedings/vast/2012/4752/0", "title": "2012 IEEE Conference on Visual Analytics Science and Technology (VAST 2012)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2011/05/ttg2011050570", "title": "How Can Visual Analytics Assist Investigative Analysis? Design Implications from an Evaluation", "doi": null, "abstractUrl": "/journal/tg/2011/05/ttg2011050570/13rRUILLkvl", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2012/11/ttg2012111992", "title": "Evaluating the Role of Time in Investigative Analysis of Document Collections", "doi": null, "abstractUrl": "/journal/tg/2012/11/ttg2012111992/13rRUwI5TQW", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__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": "trans/tg/2014/12/06875986", "title": "Supporting Communication and Coordination in Collaborative Sensemaking", "doi": null, "abstractUrl": "/journal/tg/2014/12/06875986/13rRUwwJWFN", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vast/2017/3163/0/08585484", "title": "CRICTO: Supporting Sensemaking through Crowdsourced Information Schematization", "doi": null, "abstractUrl": "/proceedings-article/vast/2017/08585484/17D45Wc1ILV", "parentPublication": { "id": "proceedings/vast/2017/3163/0", "title": "2017 IEEE Conference on Visual Analytics Science and Technology (VAST)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "mags/cg/2019/06/08889811", "title": "Provenance Analysis for Sensemaking", "doi": null, "abstractUrl": "/magazine/cg/2019/06/08889811/1eBul1FAEIE", "parentPublication": { "id": "mags/cg", "title": "IEEE Computer Graphics and Applications", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "mags/cg/2020/03/09082281", "title": "TimeSets: Temporal Sensemaking in Intelligence Analysis", "doi": null, "abstractUrl": "/magazine/cg/2020/03/09082281/1jqfbRdclvq", "parentPublication": { "id": "mags/cg", "title": "IEEE Computer Graphics and Applications", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "08023780", "articleId": "13rRUxNEqQ0", "__typename": "AdjacentArticleType" }, "next": { "fno": "08019828", "articleId": "13rRUxE04tI", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [ { "id": "17ShDTYet29", "name": "ttg201801-08017596s1.zip", "location": "https://www.computer.org/csdl/api/v1/extra/ttg201801-08017596s1.zip", "extension": "zip", "size": "31.5 MB", "__typename": "WebExtraType" } ], "articleVideos": [] }
{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUxE04tI", "doi": "10.1109/TVCG.2017.2745139", "abstract": "Sharing data for public usage requires sanitization to prevent sensitive information from leaking. Previous studies have presented methods for creating privacy preserving visualizations. However, few of them provide sufficient feedback to users on how much utility is reduced (or preserved) during such a process. To address this, we design a visual interface along with a data manipulation pipeline that allows users to gauge utility loss while interactively and iteratively handling privacy issues in their data. Widely known and discussed types of privacy models, i.e., syntactic anonymity and differential privacy, are integrated and compared under different use case scenarios. Case study results on a variety of examples demonstrate the effectiveness of our approach.", "abstracts": [ { "abstractType": "Regular", "content": "Sharing data for public usage requires sanitization to prevent sensitive information from leaking. Previous studies have presented methods for creating privacy preserving visualizations. However, few of them provide sufficient feedback to users on how much utility is reduced (or preserved) during such a process. To address this, we design a visual interface along with a data manipulation pipeline that allows users to gauge utility loss while interactively and iteratively handling privacy issues in their data. Widely known and discussed types of privacy models, i.e., syntactic anonymity and differential privacy, are integrated and compared under different use case scenarios. Case study results on a variety of examples demonstrate the effectiveness of our approach.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Sharing data for public usage requires sanitization to prevent sensitive information from leaking. Previous studies have presented methods for creating privacy preserving visualizations. However, few of them provide sufficient feedback to users on how much utility is reduced (or preserved) during such a process. To address this, we design a visual interface along with a data manipulation pipeline that allows users to gauge utility loss while interactively and iteratively handling privacy issues in their data. Widely known and discussed types of privacy models, i.e., syntactic anonymity and differential privacy, are integrated and compared under different use case scenarios. Case study results on a variety of examples demonstrate the effectiveness of our approach.", "title": "A Utility-Aware Visual Approach for Anonymizing Multi-Attribute Tabular Data", "normalizedTitle": "A Utility-Aware Visual Approach for Anonymizing Multi-Attribute Tabular Data", "fno": "08019828", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Privacy", "Data Privacy", "Syntactics", "Visualization", "Data Models", "Data Visualization", "Pipelines", "Privacy Preserving Visualization", "Utility Aware Anonymization", "Syntactic Anonymity", "Differential Privacy" ], "authors": [ { "givenName": "Xumeng", "surname": "Wang", "fullName": "Xumeng Wang", "affiliation": "Zhejiang University", "__typename": "ArticleAuthorType" }, { "givenName": "Jia-Kai", "surname": "Chou", "fullName": "Jia-Kai Chou", "affiliation": "University of California, Davis", "__typename": "ArticleAuthorType" }, { "givenName": "Wei", "surname": "Chen", "fullName": "Wei Chen", "affiliation": "Zhejiang University", "__typename": "ArticleAuthorType" }, { "givenName": "Huihua", "surname": "Guan", "fullName": "Huihua Guan", "affiliation": "Zhejiang University", "__typename": "ArticleAuthorType" }, { "givenName": "Wenlong", "surname": "Chen", "fullName": "Wenlong Chen", "affiliation": "Zhejiang University", "__typename": "ArticleAuthorType" }, { "givenName": "Tianyi", "surname": "Lao", "fullName": "Tianyi Lao", "affiliation": "Zhejiang University", "__typename": "ArticleAuthorType" }, { "givenName": "Kwan-Liu", "surname": "Ma", "fullName": "Kwan-Liu Ma", "affiliation": "University of California, Davis", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "351-360", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": 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Differential Privacy and Boosted Utility", "doi": null, "abstractUrl": "/journal/tq/2015/05/06951353/13rRUNvyaau", "parentPublication": { "id": "trans/tq", "title": "IEEE Transactions on Dependable and Secure Computing", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2019/01/08440807", "title": "GraphProtector: A Visual Interface for Employing and Assessing Multiple Privacy Preserving Graph Algorithms", "doi": null, "abstractUrl": "/journal/tg/2019/01/08440807/17D45WrVg0m", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/cvpr/2018/6420/0/642000i466", "title": "Connecting Pixels to Privacy and Utility: Automatic Redaction of Private Information in Images", "doi": null, "abstractUrl": "/proceedings-article/cvpr/2018/642000i466/17D45Wuc33S", "parentPublication": { "id": "proceedings/cvpr/2018/6420/0", "title": "2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/big-data/2022/8045/0/10020893", "title": "Anonymizing Periodical Releases of SRS Data by Fusing Differential Privacy", "doi": null, "abstractUrl": "/proceedings-article/big-data/2022/10020893/1KfQRY2YqiY", "parentPublication": { "id": "proceedings/big-data/2022/8045/0", "title": "2022 IEEE International Conference on Big Data (Big Data)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/wacv/2023/9346/0/934600e690", "title": "Interpreting Disparate Privacy-Utility Tradeoff in Adversarial Learning via Attribute Correlation", "doi": null, "abstractUrl": "/proceedings-article/wacv/2023/934600e690/1L8qvAEqT96", "parentPublication": { "id": "proceedings/wacv/2023/9346/0", "title": "2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iotdi/2020/6602/0/660200a079", "title": "RepEL: A Utility-Preserving Privacy System for IoT-Based Energy Meters", "doi": null, "abstractUrl": "/proceedings-article/iotdi/2020/660200a079/1k0P61sypFu", "parentPublication": { "id": "proceedings/iotdi/2020/6602/0", "title": "2020 IEEE/ACM Fifth International Conference on Internet-of-Things Design and Implementation (IoTDI)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2022/07/09258413", "title": "Umbra: A Visual Analysis Approach for Defense Construction Against Inference Attacks on Sensitive Information", "doi": null, "abstractUrl": "/journal/tg/2022/07/09258413/1oHhJuMoBhe", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/bibm/2020/6215/0/09313578", "title": "Embracing Differential Privacy for Anonymizing Spontaneous ADE Reporting Data", "doi": null, "abstractUrl": "/proceedings-article/bibm/2020/09313578/1qmfL6gOE1O", "parentPublication": { "id": "proceedings/bibm/2020/6215/0", "title": "2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" } ], "adjacentArticles": { "previous": { "fno": "08017596", "articleId": "13rRUytWF9s", "__typename": "AdjacentArticleType" }, "next": { "fno": "08023823", "articleId": "13rRUwbaqUU", "__typename": "AdjacentArticleType" }, "__typename": "AdjacentArticlesType" }, "webExtras": [ { "id": "17ShDTXWRJI", "name": "ttg201801-08019828s1.zip", "location": "https://www.computer.org/csdl/api/v1/extra/ttg201801-08019828s1.zip", "extension": "zip", "size": "14.9 MB", "__typename": "WebExtraType" } ], "articleVideos": [] }
{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUwbaqUU", "doi": "10.1109/TVCG.2017.2744478", "abstract": "Central to many text analysis methods is the notion of a concept: a set of semantically related keywords characterizing a specific object, phenomenon, or theme. Advances in word embedding allow building a concept from a small set of seed terms. However, naive application of such techniques may result in false positive errors because of the polysemy of natural language. To mitigate this problem, we present a visual analytics system called ConceptVector that guides a user in building such concepts and then using them to analyze documents. Document-analysis case studies with real-world datasets demonstrate the fine-grained analysis provided by ConceptVector. To support the elaborate modeling of concepts, we introduce a bipolar concept model and support for specifying irrelevant words. We validate the interactive lexicon building interface by a user study and expert reviews. Quantitative evaluation shows that the bipolar lexicon generated with our methods is comparable to human-generated ones.", "abstracts": [ { "abstractType": "Regular", "content": "Central to many text analysis methods is the notion of a concept: a set of semantically related keywords characterizing a specific object, phenomenon, or theme. Advances in word embedding allow building a concept from a small set of seed terms. However, naive application of such techniques may result in false positive errors because of the polysemy of natural language. To mitigate this problem, we present a visual analytics system called ConceptVector that guides a user in building such concepts and then using them to analyze documents. Document-analysis case studies with real-world datasets demonstrate the fine-grained analysis provided by ConceptVector. To support the elaborate modeling of concepts, we introduce a bipolar concept model and support for specifying irrelevant words. We validate the interactive lexicon building interface by a user study and expert reviews. Quantitative evaluation shows that the bipolar lexicon generated with our methods is comparable to human-generated ones.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Central to many text analysis methods is the notion of a concept: a set of semantically related keywords characterizing a specific object, phenomenon, or theme. Advances in word embedding allow building a concept from a small set of seed terms. However, naive application of such techniques may result in false positive errors because of the polysemy of natural language. To mitigate this problem, we present a visual analytics system called ConceptVector that guides a user in building such concepts and then using them to analyze documents. Document-analysis case studies with real-world datasets demonstrate the fine-grained analysis provided by ConceptVector. To support the elaborate modeling of concepts, we introduce a bipolar concept model and support for specifying irrelevant words. We validate the interactive lexicon building interface by a user study and expert reviews. Quantitative evaluation shows that the bipolar lexicon generated with our methods is comparable to human-generated ones.", "title": "ConceptVector: Text Visual Analytics via Interactive Lexicon Building Using Word Embedding", "normalizedTitle": "ConceptVector: Text Visual Analytics via Interactive Lexicon Building Using Word Embedding", "fno": "08023823", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Text Analysis", "Visual Analytics", "Semantics", "Buildings", "Computational Modeling", "Data Visualization", "Sentiment Analysis", "Text Analytics", "Visual Analytics", "Word Embedding", "Text Summarization", "Text Classification", "Concepts" ], "authors": [ { "givenName": "Deokgun", "surname": "Park", "fullName": "Deokgun Park", "affiliation": "University of Maryland, College Park, MD, USA", "__typename": "ArticleAuthorType" }, { "givenName": "Seungyeon", "surname": "Kim", "fullName": "Seungyeon Kim", "affiliation": "Google Inc., Mountain View, CA, USA", "__typename": "ArticleAuthorType" }, { "givenName": "Jurim", "surname": "Lee", "fullName": "Jurim Lee", "affiliation": "Korea University, Seoul, Republic of Korea", "__typename": "ArticleAuthorType" }, { "givenName": "Jaegul", "surname": "Choo", "fullName": "Jaegul Choo", "affiliation": "Korea University, Seoul, Republic of Korea", "__typename": "ArticleAuthorType" }, { "givenName": "Nicholas", "surname": "Diakopoulos", "fullName": "Nicholas Diakopoulos", "affiliation": "Northwestern University, Evanston, IL, USA", "__typename": "ArticleAuthorType" }, { "givenName": "Niklas", "surname": "Elmqvist", "fullName": "Niklas Elmqvist", "affiliation": "University of Maryland, College Park, MD, USA", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "361-370", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/icdmw/2016/5910/0/07836773", "title": "Lexicon Knowledge Extraction with Sentiment Polarity Computation", "doi": null, "abstractUrl": "/proceedings-article/icdmw/2016/07836773/12OmNAXxX4c", "parentPublication": { "id": "proceedings/icdmw/2016/5910/0", "title": "2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/wisa/2014/5726/0/07058024", "title": "Machine Learning and Lexicon Based Methods for Sentiment Classification: A Survey", "doi": null, "abstractUrl": "/proceedings-article/wisa/2014/07058024/12OmNBEpnvJ", "parentPublication": { "id": "proceedings/wisa/2014/5726/0", "title": "2014 11th Web Information System and Application Conference (WISA)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/icdar/1995/7128/2/71280549", "title": "READLEX: a lexicon for the recognition and analysis of structured documents", "doi": null, "abstractUrl": "/proceedings-article/icdar/1995/71280549/12OmNBsue7c", "parentPublication": { "id": "proceedings/icdar/1995/7128/2", "title": "Proceedings of 3rd International Conference on Document Analysis and Recognition", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/sera/2016/0809/0/07516126", "title": "Building thesaurus lexicon using dictionary-based approach for sentiment classification", "doi": null, "abstractUrl": "/proceedings-article/sera/2016/07516126/12OmNqBKTSm", "parentPublication": { "id": "proceedings/sera/2016/0809/0", "title": "2016 IEEE 14th International Conference on Software Engineering Research, Management and Applications (SERA)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/das/2018/3346/0/3346a001", "title": "Word Spotting and Recognition Using Deep Embedding", "doi": null, "abstractUrl": "/proceedings-article/das/2018/3346a001/12OmNwbLVlw", "parentPublication": { "id": "proceedings/das/2018/3346/0", "title": "2018 13th IAPR International Workshop on Document Analysis Systems (DAS)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/ictcs/2017/0527/0/0527a241", "title": "Building Arabic Polarizerd Lexicon from Rated Online Customer Reviews", "doi": null, "abstractUrl": "/proceedings-article/ictcs/2017/0527a241/12OmNx5Yvs7", "parentPublication": { "id": "proceedings/ictcs/2017/0527/0", "title": "2017 International Conference on New Trends in Computing Sciences (ICTCS)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/acling/2015/9154/0/07422285", "title": "Automatic Expandable Large-Scale Sentiment Lexicon of Modern Standard Arabic and Colloquial", "doi": null, "abstractUrl": "/proceedings-article/acling/2015/07422285/12OmNyLiurE", "parentPublication": { "id": "proceedings/acling/2015/9154/0", "title": "2015 First International Conference on Arabic Computational Linguistics (ACLing)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/wi-iat/2014/4143/1/4143a392", "title": "Tweet Sentiment Analytics with Context Sensitive Tone-Word Lexicon", "doi": null, "abstractUrl": "/proceedings-article/wi-iat/2014/4143a392/12OmNyOq56A", "parentPublication": { "id": "wi-iat/2014/4143/1", "title": "2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/skg/2012/4794/0/4794a241", "title": "An Improved Method to Building a Score Lexicon for Chinese Sentiment Analysis", "doi": null, "abstractUrl": "/proceedings-article/skg/2012/4794a241/12OmNzahc09", "parentPublication": { "id": "proceedings/skg/2012/4794/0", "title": 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{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUwI5U2P", "doi": "10.1109/TVCG.2017.2745118", "abstract": "PhenoLines is a visual analysis tool for the interpretation of disease subtypes, derived from the application of topic models to clinical data. Topic models enable one to mine cross-sectional patient comorbidity data (e.g., electronic health records) and construct disease subtypes—each with its own temporally evolving prevalence and co-occurrence of phenotypes—without requiring aligned longitudinal phenotype data for all patients. However, the dimensionality of topic models makes interpretation challenging, and de facto analyses provide little intuition regarding phenotype relevance or phenotype interrelationships. PhenoLines enables one to compare phenotype prevalence within and across disease subtype topics, thus supporting subtype characterization, a task that involves identifying a proposed subtype's dominant phenotypes, ages of effect, and clinical validity. We contribute a data transformation workflow that employs the Human Phenotype Ontology to hierarchically organize phenotypes and aggregate the evolving probabilities produced by topic models. We introduce a novel measure of phenotype relevance that can be used to simplify the resulting topology. The design of PhenoLines was motivated by formative interviews with machine learning and clinical experts. We describe the collaborative design process, distill high-level tasks, and report on initial evaluations with machine learning experts and a medical domain expert. These results suggest that PhenoLines demonstrates promising approaches to support the characterization and optimization of topic models.", "abstracts": [ { "abstractType": "Regular", "content": "PhenoLines is a visual analysis tool for the interpretation of disease subtypes, derived from the application of topic models to clinical data. Topic models enable one to mine cross-sectional patient comorbidity data (e.g., electronic health records) and construct disease subtypes—each with its own temporally evolving prevalence and co-occurrence of phenotypes—without requiring aligned longitudinal phenotype data for all patients. However, the dimensionality of topic models makes interpretation challenging, and de facto analyses provide little intuition regarding phenotype relevance or phenotype interrelationships. PhenoLines enables one to compare phenotype prevalence within and across disease subtype topics, thus supporting subtype characterization, a task that involves identifying a proposed subtype's dominant phenotypes, ages of effect, and clinical validity. We contribute a data transformation workflow that employs the Human Phenotype Ontology to hierarchically organize phenotypes and aggregate the evolving probabilities produced by topic models. We introduce a novel measure of phenotype relevance that can be used to simplify the resulting topology. The design of PhenoLines was motivated by formative interviews with machine learning and clinical experts. We describe the collaborative design process, distill high-level tasks, and report on initial evaluations with machine learning experts and a medical domain expert. These results suggest that PhenoLines demonstrates promising approaches to support the characterization and optimization of topic models.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "PhenoLines is a visual analysis tool for the interpretation of disease subtypes, derived from the application of topic models to clinical data. Topic models enable one to mine cross-sectional patient comorbidity data (e.g., electronic health records) and construct disease subtypes—each with its own temporally evolving prevalence and co-occurrence of phenotypes—without requiring aligned longitudinal phenotype data for all patients. However, the dimensionality of topic models makes interpretation challenging, and de facto analyses provide little intuition regarding phenotype relevance or phenotype interrelationships. PhenoLines enables one to compare phenotype prevalence within and across disease subtype topics, thus supporting subtype characterization, a task that involves identifying a proposed subtype's dominant phenotypes, ages of effect, and clinical validity. We contribute a data transformation workflow that employs the Human Phenotype Ontology to hierarchically organize phenotypes and aggregate the evolving probabilities produced by topic models. We introduce a novel measure of phenotype relevance that can be used to simplify the resulting topology. The design of PhenoLines was motivated by formative interviews with machine learning and clinical experts. We describe the collaborative design process, distill high-level tasks, and report on initial evaluations with machine learning experts and a medical domain expert. These results suggest that PhenoLines demonstrates promising approaches to support the characterization and optimization of topic models.", "title": "PhenoLines: Phenotype Comparison Visualizations for Disease Subtyping via Topic Models", "normalizedTitle": "PhenoLines: Phenotype Comparison Visualizations for Disease Subtyping via Topic Models", "fno": "08019821", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Diseases", "Data Models", "Visualization", "Biological System Modeling", "Analytical Models", "Data Visualization", "Tools", "Developmental Disorder", "Human Phenotype Ontology HPO", "Phenotypes", "Topic Models", "Topology Simplification" ], "authors": [ { "givenName": "Michael", "surname": "Glueck", "fullName": "Michael Glueck", "affiliation": "Autodesk Research and University, Toronto", "__typename": "ArticleAuthorType" }, { "givenName": "Mahdi Pakdaman", "surname": "Naeini", "fullName": "Mahdi Pakdaman Naeini", "affiliation": "Harvard University", "__typename": "ArticleAuthorType" }, { "givenName": "Finale", "surname": "Doshi-Velez", "fullName": "Finale Doshi-Velez", "affiliation": "Harvard University", "__typename": "ArticleAuthorType" }, { "givenName": "Fanny", "surname": "Chevalier", "fullName": "Fanny Chevalier", "affiliation": "Inria", "__typename": "ArticleAuthorType" }, { "givenName": "Azam", "surname": "Khan", "fullName": "Azam Khan", "affiliation": "Autodesk Research", "__typename": "ArticleAuthorType" }, { "givenName": "Daniel", "surname": "Wigdor", "fullName": "Daniel Wigdor", "affiliation": "University of Toronto", "__typename": "ArticleAuthorType" }, { "givenName": "Michael", "surname": "Brudno", "fullName": "Michael Brudno", "affiliation": "Hospital for Sick ChildrenUniversity of Toronto", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "371-381", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/cbms/2017/1710/0/1710a358", "title": "Extracting Disease-Phenotype Relations from Text with Disease-Phenotype Concept Recognisers and Association Rule Mining", "doi": null, "abstractUrl": "/proceedings-article/cbms/2017/1710a358/12OmNANTAsy", "parentPublication": { "id": "proceedings/cbms/2017/1710/0", "title": "2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/bibmw/2010/8303/0/05703808", "title": "Clustering-based methodology with minimal user supervision for displaying cell-phenotype signatures in image-based screening", "doi": null, "abstractUrl": "/proceedings-article/bibmw/2010/05703808/12OmNCdk2L4", "parentPublication": { "id": "proceedings/bibmw/2010/8303/0", "title": "2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/iscc/2017/1629/0/08024647", "title": "Weighted Graph Constraint and Group Centric Non-negative Matrix Factorization for gene-phenotype association prediction", "doi": null, "abstractUrl": "/proceedings-article/iscc/2017/08024647/12OmNCesram", "parentPublication": { "id": "proceedings/iscc/2017/1629/0", "title": "2017 IEEE Symposium on Computers and Communications (ISCC)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/bibm/2012/2559/0/06392679", "title": "A multi-objective program for quantitative subtyping of clinically relevant phenotypes", "doi": null, "abstractUrl": "/proceedings-article/bibm/2012/06392679/12OmNx4gUw6", "parentPublication": { "id": "proceedings/bibm/2012/2559/0", "title": "2012 IEEE International Conference on Bioinformatics and Biomedicine", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/bibm/2017/3050/0/08217911", "title": "Measuring phenotype-phenotype similarity through the interactome", "doi": null, "abstractUrl": "/proceedings-article/bibm/2017/08217911/12OmNxdVgQc", "parentPublication": { "id": "proceedings/bibm/2017/3050/0", "title": "2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/bibm/2013/1309/0/06732509", "title": "Multi-view biclustering for genotype-phenotype association studies of complex diseases", "doi": null, "abstractUrl": "/proceedings-article/bibm/2013/06732509/12OmNyugyNH", "parentPublication": { "id": "proceedings/bibm/2013/1309/0", "title": "2013 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2017/01/07534774", "title": "PhenoStacks: Cross-Sectional Cohort Phenotype Comparison Visualizations", "doi": null, "abstractUrl": "/journal/tg/2017/01/07534774/13rRUy2YLYB", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "trans/tg/2016/01/07192670", "title": "PhenoBlocks: Phenotype Comparison Visualizations", "doi": null, "abstractUrl": "/journal/tg/2016/01/07192670/13rRUyYSWt0", "parentPublication": { "id": "trans/tg", "title": "IEEE Transactions on Visualization & Computer Graphics", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/bibm/2022/6819/0/09995118", "title": "Phenotype Prediction by Heterogeneous Molecular Network Embedding", "doi": null, "abstractUrl": "/proceedings-article/bibm/2022/09995118/1JC2DOPYJiw", "parentPublication": { "id": "proceedings/bibm/2022/6819/0", 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We abstract the model complexity in an interactive visual workspace for exploring the automatic matching results of two models, investigating topic summaries, analyzing parameter distributions, and reviewing documents. The main contribution of our work is an iterative decision-making technique in which users provide a document-based relevance feedback that allows the framework to converge to a user-endorsed topic distribution. We also report feedback from a two-stage study which shows that our technique results in topic model quality improvements on two independent measures.", "abstracts": [ { "abstractType": "Regular", "content": "Topic modeling algorithms are widely used to analyze the thematic composition of text corpora but remain difficult to interpret and adjust. Addressing these limitations, we present a modular visual analytics framework, tackling the understandability and adaptability of topic models through a user-driven reinforcement learning process which does not require a deep understanding of the underlying topic modeling algorithms. Given a document corpus, our approach initializes two algorithm configurations based on a parameter space analysis that enhances document separability. We abstract the model complexity in an interactive visual workspace for exploring the automatic matching results of two models, investigating topic summaries, analyzing parameter distributions, and reviewing documents. The main contribution of our work is an iterative decision-making technique in which users provide a document-based relevance feedback that allows the framework to converge to a user-endorsed topic distribution. We also report feedback from a two-stage study which shows that our technique results in topic model quality improvements on two independent measures.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Topic modeling algorithms are widely used to analyze the thematic composition of text corpora but remain difficult to interpret and adjust. Addressing these limitations, we present a modular visual analytics framework, tackling the understandability and adaptability of topic models through a user-driven reinforcement learning process which does not require a deep understanding of the underlying topic modeling algorithms. Given a document corpus, our approach initializes two algorithm configurations based on a parameter space analysis that enhances document separability. We abstract the model complexity in an interactive visual workspace for exploring the automatic matching results of two models, investigating topic summaries, analyzing parameter distributions, and reviewing documents. The main contribution of our work is an iterative decision-making technique in which users provide a document-based relevance feedback that allows the framework to converge to a user-endorsed topic distribution. 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{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUB7a1fY", "doi": "10.1109/TVCG.2017.2744359", "abstract": "Color is frequently used to encode values in visualizations. For color encodings to be effective, the mapping between colors and values must preserve important differences in the data. However, most guidelines for effective color choice in visualization are based on either color perceptions measured using large, uniform fields in optimal viewing environments or on qualitative intuitions. These limitations may cause data misinterpretation in visualizations, which frequently use small, elongated marks. Our goal is to develop quantitative metrics to help people use color more effectively in visualizations. We present a series of crowdsourced studies measuring color difference perceptions for three common mark types: points, bars, and lines. Our results indicate that peoples' abilities to perceive color differences varies significantly across mark types. Probabilistic models constructed from the resulting data can provide objective guidance for designers, allowing them to anticipate viewer perceptions in order to inform effective encoding design.", "abstracts": [ { "abstractType": "Regular", "content": "Color is frequently used to encode values in visualizations. For color encodings to be effective, the mapping between colors and values must preserve important differences in the data. However, most guidelines for effective color choice in visualization are based on either color perceptions measured using large, uniform fields in optimal viewing environments or on qualitative intuitions. These limitations may cause data misinterpretation in visualizations, which frequently use small, elongated marks. Our goal is to develop quantitative metrics to help people use color more effectively in visualizations. We present a series of crowdsourced studies measuring color difference perceptions for three common mark types: points, bars, and lines. Our results indicate that peoples' abilities to perceive color differences varies significantly across mark types. Probabilistic models constructed from the resulting data can provide objective guidance for designers, allowing them to anticipate viewer perceptions in order to inform effective encoding design.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Color is frequently used to encode values in visualizations. For color encodings to be effective, the mapping between colors and values must preserve important differences in the data. However, most guidelines for effective color choice in visualization are based on either color perceptions measured using large, uniform fields in optimal viewing environments or on qualitative intuitions. These limitations may cause data misinterpretation in visualizations, which frequently use small, elongated marks. Our goal is to develop quantitative metrics to help people use color more effectively in visualizations. We present a series of crowdsourced studies measuring color difference perceptions for three common mark types: points, bars, and lines. Our results indicate that peoples' abilities to perceive color differences varies significantly across mark types. Probabilistic models constructed from the resulting data can provide objective guidance for designers, allowing them to anticipate viewer perceptions in order to inform effective encoding design.", "title": "Modeling Color Difference for Visualization Design", "normalizedTitle": "Modeling Color Difference for Visualization Design", "fno": "08017604", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Image Color Analysis", "Color", "Encoding", "Visualization", "Measurement", "Data Visualization", "Computational Modeling", "Color Perception", "Graphical Perception", "Color Models", "Crowdsourcing" ], "authors": [ { "givenName": "Danielle Albers", "surname": "Szafir", "fullName": "Danielle Albers Szafir", "affiliation": "University of Colorado", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "392-401", "year": "2018", 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{ "issue": { "id": "12OmNCaLEju", "title": "Jan.", "year": "2018", "issueNum": "01", "idPrefix": "tg", "pubType": "journal", "volume": "24", "label": "Jan.", "downloadables": { "hasCover": false, "__typename": "PeriodicalIssueDownloadablesType" }, "__typename": "PeriodicalIssue" }, "article": { "id": "13rRUy3gn7C", "doi": "10.1109/TVCG.2017.2744184", "abstract": "Traditional scatterplots fail to scale as the complexity and amount of data increases. In response, there exist many design options that modify or expand the traditional scatterplot design to meet these larger scales. This breadth of design options creates challenges for designers and practitioners who must select appropriate designs for particular analysis goals. In this paper, we help designers in making design choices for scatterplot visualizations. We survey the literature to catalog scatterplot-specific analysis tasks. We look at how data characteristics influence design decisions. We then survey scatterplot-like designs to understand the range of design options. Building upon these three organizations, we connect data characteristics, analysis tasks, and design choices in order to generate challenges, open questions, and example best practices for the effective design of scatterplots.", "abstracts": [ { "abstractType": "Regular", "content": "Traditional scatterplots fail to scale as the complexity and amount of data increases. In response, there exist many design options that modify or expand the traditional scatterplot design to meet these larger scales. This breadth of design options creates challenges for designers and practitioners who must select appropriate designs for particular analysis goals. In this paper, we help designers in making design choices for scatterplot visualizations. We survey the literature to catalog scatterplot-specific analysis tasks. We look at how data characteristics influence design decisions. We then survey scatterplot-like designs to understand the range of design options. Building upon these three organizations, we connect data characteristics, analysis tasks, and design choices in order to generate challenges, open questions, and example best practices for the effective design of scatterplots.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Traditional scatterplots fail to scale as the complexity and amount of data increases. In response, there exist many design options that modify or expand the traditional scatterplot design to meet these larger scales. This breadth of design options creates challenges for designers and practitioners who must select appropriate designs for particular analysis goals. In this paper, we help designers in making design choices for scatterplot visualizations. We survey the literature to catalog scatterplot-specific analysis tasks. We look at how data characteristics influence design decisions. We then survey scatterplot-like designs to understand the range of design options. 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The first considers how the common elements of comparison—a target set of items that are related and an action the user wants to perform on that relationship—are present in an analysis problem. The second considers why these elements lead to challenges because of their scale, in number of items, complexity of items, or complexity of relationship. The third considers what strategies address the identified scaling challenges, grouping solutions into three broad categories. The fourth considers which visual designs map to these strategies to provide solutions for a comparison analysis problem. In sequence, these considerations provide a process for developers to consider support for comparison in the design of visualization tools. Case studies show how these considerations can help in the design and evaluation of visualization solutions for comparison problems.", "abstracts": [ { "abstractType": "Regular", "content": "Supporting comparison is a common and diverse challenge in visualization. Such support is difficult to design because solutions must address both the specifics of their scenario as well as the general issues of comparison. This paper aids designers by providing a strategy for considering those general issues. It presents four considerations that abstract comparison. These considerations identify issues and categorize solutions in a domain independent manner. The first considers how the common elements of comparison—a target set of items that are related and an action the user wants to perform on that relationship—are present in an analysis problem. The second considers why these elements lead to challenges because of their scale, in number of items, complexity of items, or complexity of relationship. The third considers what strategies address the identified scaling challenges, grouping solutions into three broad categories. The fourth considers which visual designs map to these strategies to provide solutions for a comparison analysis problem. In sequence, these considerations provide a process for developers to consider support for comparison in the design of visualization tools. Case studies show how these considerations can help in the design and evaluation of visualization solutions for comparison problems.", "__typename": "ArticleAbstractType" } ], "normalizedAbstract": "Supporting comparison is a common and diverse challenge in visualization. Such support is difficult to design because solutions must address both the specifics of their scenario as well as the general issues of comparison. This paper aids designers by providing a strategy for considering those general issues. It presents four considerations that abstract comparison. These considerations identify issues and categorize solutions in a domain independent manner. The first considers how the common elements of comparison—a target set of items that are related and an action the user wants to perform on that relationship—are present in an analysis problem. The second considers why these elements lead to challenges because of their scale, in number of items, complexity of items, or complexity of relationship. The third considers what strategies address the identified scaling challenges, grouping solutions into three broad categories. The fourth considers which visual designs map to these strategies to provide solutions for a comparison analysis problem. In sequence, these considerations provide a process for developers to consider support for comparison in the design of visualization tools. Case studies show how these considerations can help in the design and evaluation of visualization solutions for comparison problems.", "title": "Considerations for Visualizing Comparison", "normalizedTitle": "Considerations for Visualizing Comparison", "fno": "08017615", "hasPdf": true, "idPrefix": "tg", "keywords": [ "Visualization", "Tools", "Data Visualization", "Electronic Mail", "Complexity Theory", "Encoding", "Information Visualization", "Comparison", "Taxonomies", "Visualization Models", "Task Analysis" ], "authors": [ { "givenName": "Michael", "surname": "Gleicher", "fullName": "Michael Gleicher", "affiliation": "University of Wisconsin-Madison", "__typename": "ArticleAuthorType" } ], "replicability": null, "showBuyMe": true, "showRecommendedArticles": true, "isOpenAccess": false, "issueNum": "01", "pubDate": "2018-01-01 00:00:00", "pubType": "trans", "pages": "413-423", "year": "2018", "issn": "1077-2626", "isbn": null, "notes": null, "notesType": null, "__typename": "ArticleType" }, "recommendedArticles": [ { "id": "proceedings/ismvl/2014/3535/0/3534a025", "title": "Multiple-Valued Problem Solvers -- Comparison of Several Approaches", "doi": null, "abstractUrl": "/proceedings-article/ismvl/2014/3534a025/12OmNANTAxe", "parentPublication": { "id": "proceedings/ismvl/2014/3535/0", "title": "2014 IEEE 44th International Symposium on Multiple-Valued Logic (ISMVL)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/vr/2016/0836/0/07504691", "title": "Adaptive information density for augmented reality displays", "doi": null, "abstractUrl": "/proceedings-article/vr/2016/07504691/12OmNBQC89A", "parentPublication": { "id": "proceedings/vr/2016/0836/0", "title": "2016 IEEE Virtual Reality (VR)", "__typename": "ParentPublication" }, "__typename": "RecommendedArticleType" }, { "id": "proceedings/wcre/2008/3429/0/3429a229", "title": "Variant Comparison - 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