Miracle-dz/UniFAR-FTUs huggingface dataset:
Loop Closure in 2D LIDAR and RGB-D SLAM

According to the advantages of different sensors, it can improve the speed and accuracy of Simultaneous Localization and Mapping (SLAM) based on multi-sensor information. However, with the accumulation of time, the error will gradually increase due to the factors of environment and hardware in Mapping. Therefore, the paper proposes a loop closure algorithm based on the combination of 2D LIDAR and RGB-D camera. The algorithm will create a grid map by the use of 2D LIDAR, and use a coarse-to-fine matching method on the candidate region. Firstly, it will get the RGB-D image of the current location and compare the global descriptors of the RGB image using the similarity evaluation based on distance. In the initial screening stage, part of the RGB image in the map storage with a high similarity to the RGB image at the current location will be selected. Secondly, use local descriptors to compare and extract the most similar RGB image, thus establish the corresponding relationship between the RGB images. Finally, the depth image corresponding to the RGB image is segmented through the local descriptors, and adjust the relative pose according to the point cloud matching technology to obtain a robust loop closure algorithm.
Interpretable Time-Dependent Convolutional Emotion Recognition with Contextual Data Streams

Emotion prediction is important when interacting with computers. However, emotions are complex, difficult to assess, understand, and hard to classify. Current emotion classification strategies skip why a specific emotion was predicted, complicating the user’s understanding of affective and empathic interface behaviors. Advances in deep learning showed that convolutional networks can learn powerful time-series patterns while showing classification decisions and feature importances. We present a novel convolution-based model that classifies emotions robustly. Our model not only offers high emotion-prediction performance but also enables transparency on the model decisions. Our solution thereby provides a time-aware feature interpretation of classification decisions using saliency maps. We evaluate the system on a contextual, real-world driving dataset involving twelve participants. Our model achieves a mean accuracy of in 5-class emotion classification on unknown roads and outperforms in-car facial expression recognition by . We conclude how emotion prediction can be improved by incorporating emotion sensing into interactive computing systems.
Understanding Physical Breakdowns in Virtual Reality

Virtual Reality (VR) moves away from well-controlled laboratory environments into public and personal spaces. As users are visually disconnected from the physical environment, interacting in an uncontrolled space frequently leads to collisions and raises safety concerns. In my thesis, I investigate this phenomenon which I define as the physical breakdown in VR. The goal is to understand the reasons for physical breakdowns, provide solutions, and explore future mechanisms that could perpetuate safety risks. First, I explored the reasons for physical breakdowns by investigating how people interact with the current VR safety mechanism (e.g., Oculus Guardian). Results show one reason for breaking out of the safety boundary is when interacting with large motions (e.g., swinging arms), the user does not have enough time to react although they see the safety boundary. I proposed a solution, FingerMapper, that maps small-scale finger motions onto virtual arms and hands to enable whole-body virtual arm motions in VR to avoid physical breakdowns. To demonstrate future safety risks, I explored the malicious use of perceptual manipulations (e.g., redirection techniques) in VR, which could deliberately create physical breakdowns without users noticing. Results indicate further open challenges about the cognitive process of how users comprehend their physical environment when they are blindfolded in VR.
Expressiveness, Cost, and Collectivism: How the Design of Preference Languages Shapes Participation in Algorithmic Decision-Making

Emerging methods for participatory algorithm design have proposed collecting and aggregating individual stakeholders’ preferences to create algorithmic systems that account for those stakeholders’ values. Drawing on two years of research across two public school districts in the United States, we study how families and school districts use students’ preferences for schools to meet their goals in the context of algorithmic student assignment systems. We find that the design of the preference language, i.e. the structure in which participants must express their needs and goals to the decision-maker, shapes the opportunities for meaningful participation. We define three properties of preference languages – expressiveness, cost, and collectivism – and discuss how these factors shape who is able to participate, and the extent to which they are able to effectively communicate their needs to the decision-maker. Reflecting on these findings, we offer implications and paths forward for researchers and practitioners who are considering applying a preference-based model for participation in algorithmic decision making.
A Literature Review of Video-Sharing Platform Research in HCI

Video-sharing platforms (VSPs) such as YouTube, TikTok, and Twitch have grown rapidly in recent years and attracted millions of users. Research topics such as online communities, video interactions, and recommendation algorithms have drawn increasing attention. Group and community dynamics were also examined with live streaming and short-form videos. However, HCI literature lacks a holistic picture of video-sharing research themes, methods, and findings that summarizes the diverse topics on interaction modalities and communities. Prior reviews on VSPs were about a particular platform or reviewed as a part of social media. This paper contributes a scoping review of 106 articles on video-sharing published in HCI literature from 2012 to June 2022. We identified six research themes through grounded theory analysis and encoded five HCI research methods in VSP studies. We concluded a framework with five components to structure findings in video-sharing research, with which we reflect on future directions on this topic.
Robust and efficient monolithic fluid‐structure‐interaction solvers

We construct new robust and efficient preconditioned generalized minimal residual solvers for the monolithic linear systems of algebraic equations arising from the finite element discretization and Newton's linearization of the fully coupled fluid–structure interaction system of partial differential equations in the arbitrary Lagrangian–Eulerian formulation. We admit both linear elastic and nonlinear hyperelastic materials in the solid model and cover a large range of flows, for example, water, blood, and air, with highly varying density. The preconditioner is constructed in form of L̂D̂Û , where L̂ , D̂ , and Û are proper approximations to the matrices L, D, and U in the LDU block factorization of the fully coupled system matrix, respectively. The inverse of the corresponding Schur complement is approximated by applying a few cycles of a special class of algebraic multigrid methods to the perturbed fluid sub‐problem, which is obtained by modifying corresponding entries in the original fluid matrix with an explicitly constructed approximation to the exact perturbation coming from the sparse matrix–matrix multiplications. The numerical studies presented impressively demonstrate the robustness and the efficiency of the preconditioner proposed in the paper. Copyright © 2016 John Wiley & Sons, Ltd.
Evaluating Mobile Apps Targeting Personal Goals

Goals are fundamental to everyday life and are reflected in the growing HCI research in personal informatics and behaviour change. Besides academic work, a wealth of commercial mobile apps have also been developed to support users in setting their goals and achieving them. Despite their popularity, such apps, however, have been limitedly evaluated. We report a functionality review grounded in auto-ethnography and expert evaluation of the 21 most popular such apps selected from 1336 apps on the Google Play Store. We used a hybrid approach based on goal-setting theory for the evaluation. Findings indicate the more nuanced functionality of goal capturing, extending those explored in previous work for goal setting, monitoring and maintaining motivation. They also highlight the importance of distinguishing between high and low-level goals and their domains since most apps support multiple rather than individual goals. We conclude with design implications to support the setting of multiple personal goals at both high and low levels and across different domains, the use of consistent terms for distinguishing goals at different levels, and for visualizing the relationships among multiple goals.
How to Write Better CHI Papers (with LaTeX in Overleaf)

Writing and organizing research papers is a valuable skill that can make or break your academic career. This course will help you improve your skills in writing research papers for publication at CHI. In the past five years, my writing course at CHI has introduced you to everything you wanted to know about writing papers. Now, it is time to take your skills even further. This course is now also about how to use LaTeX and Overleaf to format your papers so that they are easy to read and have the most practical impact. It is broken up into four 75-minute online units that will help you structure your paper’s research content and typographic design. The goal of the course is to help you write something that makes a contribution to the field of human-computer interaction and can be understood by other HCI researchers through engaging formatting and concise language.
A Usability Evaluation of AFL and libFuzzer with CS Students

In top-tier companies and academia, fuzzing has established itself as a valuable tool for finding bugs. It is a tool created by experts for experts, and a lot of research is being invested into improving the power of fuzzing. However, the usability of fuzzing has not received much attention yet. To alleviate this, we evaluated the usability of two popular fuzzers: AFL and libFuzzer. In our fuzzing study, 47 computer science students each worked up to 20 hours in total. We found significant usability challenges for both fuzzers leading to only 17 participants who were able to finish all tasks. Even the successful participants struggled with some of the necessary steps and found them complex and confusing. While on the whole, AFL fared better than libFuzzer, both fuzzers have strengths and weaknesses and can be improved based on our results.
CatHill: Emotion-Based Interactive Storytelling Game as a Digital Mental Health Intervention

In this paper, we introduce CatHill, an emotion-based interactive storytelling game leveraging Cognitive Behavioral Therapy (CBT) to help college students with chronic mental health conditions. The game utilizes evidence-based stories to integrate three CBT techniques: exposure therapy, cognitive restructuring, and relaxation training. We propose a novel interface only controlled by players’ mouths to engage players better. The game allows players to chat with non-player characters (NPCs) and their speech emotions will deeply influence NPCs’ actions and story progression. Besides, players can also conduct mindful breathing exercises by breath control. Such fun and impressive interaction modes teach young people to understand the correlation among thoughts, emotions, and behaviors and change irrational automatic thoughts, and overcome anxiety or distress. Through our practice, we show that popular game elements and new interaction technologies have the potential to expand the impact of digital mental health interventions.
Organizing Community-based Events in Participatory Action Research: Lessons Learned from a Photovoice Exhibition

Participatory action research (PAR) approaches center community members’ lived experiences and can spur positive change around pressing challenges faced by communities. Even though PAR and similar approaches have been increasingly adopted in HCI research that focuses on social justice and community empowerment, public-facing events that are based on this research and center community members’ voices are less common. This case study sheds light on how to initiate and organize events that build on existing PAR efforts, and what practical challenges might exist in this process. Building on a photovoice research project, we—a collaborative team of university researchers and staff members of a community organization in Eastside Detroit—co-organized a community-based public-facing exhibition that featured community members’ photographic narratives of personal and communal safety and surveillance. In this case study, we reflect on the challenges we experienced in planning and holding the exhibition. We contribute a set of practical guidelines to help researchers facilitate community-based events when conducting participatory action research in HCI.
I Need a Third Arm! Eliciting Body-based Interactions with a Wearable Robotic Arm

Wearable robotic arms (WRA) open up a unique interaction space that closely integrates the user’s body with an embodied robotic collaborator. This space affords diverse interaction styles, including body movement, hand gestures, or gaze. Yet, it is so-far unexplored which commands are desirable from a user perspective. Contributing findings from an elicitation study (N=14), we provide a comprehensive set of interactions for basic robot control, navigation, object manipulation, and emergency situations, performed when hands are free or occupied. Our study provides insights into preferred body parts, input modalities, and the users’ underlying sources of inspiration. Comparing interaction styles between WRAs and off-body robots, we highlight how WRAs enable a range of interactions specific for on-body robots and how users use WRAs both as tools and as collaborators. We conclude by providing guidance on the design of ad-hoc interaction with WRAs informed by user behavior.
Literature Reviews in HCI: A Review of Reviews

This paper analyses Human-Computer Interaction (HCI) literature reviews to provide a clear conceptual basis for authors, reviewers, and readers. HCI is multidisciplinary and various types of literature reviews exist, from systematic to critical reviews in the style of essays. Yet, there is insufficient consensus of what to expect of literature reviews in HCI. Thus, a shared understanding of literature reviews and clear terminology is needed to plan, evaluate, and use literature reviews, and to further improve review methodology. We analysed 189 literature reviews published at all SIGCHI conferences and ACM Transactions on Computer-Human Interaction (TOCHI) up until August 2022. We report on the main dimensions of variation: (i) contribution types and topics; and (ii) structure and methodologies applied. We identify gaps and trends to inform future meta work in HCI and provide a starting point on how to move towards a more comprehensive terminology system of literature reviews in HCI.
Tactilient: Turbulence resilient tactile icons for pilot feedback

Given the high attentional demand in aircraft cockpits, tactons can be used to deliver information without overloading the visual and auditory channels. However, aircraft are subject to turbulence that interfere with vibrotactile feedback. To investigate the impact of turbulence on tacton identification, 18 participants tried to identify 9 tactons with varying intensity and rhythm, while experiencing uncomfortable and very uncomfortable levels of mechanical vibration defined in ISO 2631-1. The results show that the effectiveness of tactile communication decreases with the rhythm identification performance as the level of turbulence increases. In our study, an RMS acceleration delta of 0.70 Grms between two consecutive tactons guaranteed near zero confusion. Based on their experience performing the study, participants built tactons that included 4 pulses, lasted for at least 350 ms and vibrated at no less than 1.25 Grms to be comfortably perceived. Our results will support practitioners for designing tactons that can be more resilient to turbulence.
Overcoming the Pitfalls of HPC-based Cryptojacking Detection in Presence of GPUs

With the rising number of devices connected to the internet, the number of cyber-attacks on these devices increases in parallel. There are several strategies that an attacker can pursue, like stealing intellectual property of a victim or encrypting data to demand ransom for the decryption. In this work, we are focusing on the detection of so called cryptojacking attacks, in which an attacker that gained access to a system, then introduces programs that use the processing power of the victim device to mine cryptocurrencies. The presence of such an attack is not obvious right away and the longer an attacker manages to remain undetected, the longer they can profit having the victim foot the power bill. In this study, we combine previous approaches to demonstrate that cryptojacking attacks can be detected with an accuracy of 96% by leveraging hardware performance counters on the Windows operating system. Further, we present a method to determine which performance events result in the best detection rates, thus allowing the selection of a few performance events that can be monitored simultaneously by modern consumer CPUs. In a next step, we show that the CPU counters-based detection mechanism fails when an attacker switches from using the CPU resources to GPUs for the mining tasks. Based on these findings we then improve the previous detection approaches by extending the CPU performance counters with GPU-specific metrics resulting in 99.86% accuracy for the GPU-based cryptojacking attack class. In addition to a high detection rate the presented approach only causes a negligible performance loss while monitoring the whole system, which allows for continuous monitoring of live systems.
NotiFade: Minimizing OHMD Notification Distractions Using Fading

While animations can minimize attention costs for desktop notifications, their application for Optical see-through Head-Mounted Display (OHMD) notifications is underexplored. To investigate the effectiveness of animation on OHMD notifications in minimizing attention costs, we conducted a study comparing fade-in, blast, and scrolling notification animations. Results showed that fade-in animation minimizes notification interference with the primary task, unlike blast and scrolling animations. Its effectiveness depends on multiple factors, including fade-duration and location of the primary task. Finally, we discuss how fade-in animation can improve OHMD notifications and its associated trade-offs.
Supervising Multiple Operating Rooms Using a Head-Worn display: A Longitudinal Evaluation of the Experience of Supervising Anesthesiologists and Their Co-Workers

Research has explored head-worn displays (HWD) in various professional contexts. However, evaluations have been limited by short-term use, a focus on the person using the HWD, and on performance variables. In a field study, we evaluated a monocular, opaque HWD for multi-patient monitoring, which supervising anesthesiologists wore for 8-10 days each. We investigated the effect of prolonged HWD use on the experience of the supervising anesthesiologists and their co-workers using interviews and repeated observations. A reflexive thematic analysis showed (1) interaction and mindset changes over time, (2) information on the HWD is more than numbers, (3) the HWD affects co-workers' collaboration with supervisors, and (4) distraction depends on the point of view. Using activity theory, we discuss the fact that HWD use develops and changes over time and that even a single-user HWD influences the collaboration with co-workers. We conclude with implications for HWD design, implementation, and evaluation.
Identifying Multimodal Context Awareness Requirements for Supporting User Interaction with Procedural Videos

Following along how-to videos requires alternating focus between understanding procedural video instructions and performing them. Examining how to support these continuous context switches for the user has been largely unexplored. In this paper, we describe a user study with thirty participants who performed an hour-long cooking task while interacting with a wizard-of-oz hands-free interactive system that is aware of both their cooking progress and environment contexts. Through analysis of the session scripts, we identify a dichotomy between participant query differences and workflow alignment similarities, under-studied interactions that require AI functionality beyond video navigation alone, and queries that call for multimodal sensing of a user’s environment. By understanding the assistant experience through the participants’ interactions, we identify design implications for a smart assistant that can discern a user’s task completion flow and personal characteristics, accommodate requests within and external to the task domain, and support nonvoice-based queries.
It’s About Time: Attending to Temporality in Misinformation Interventions

Recent studies in HCI have explored how we might reduce the spread of online misinformation by helping people learn how to evaluate information in more skillful ways. Unfortunately, it isn’t clear that such interventions have been meaningfully integrated into communities. To better understand why this is the case, this paper engages over thirty information professionals (educators, librarians, and journalists) who promote digital literacy in BIPOC and rural communities. Our participants describe a temporal mismatch, whereby digital literacy requires time-consuming processes that cannot be accelerated, but institutional and societal pressures demand speed. We also describe strategies that participants envisaged to cope with this mismatch. This leads us to discuss how the HCI community can better engage with the temporal aspects of digital literacy work, with a view toward expanding the range of solutions we can design to address the misinformation crisis.
Exploring Shape Designs for Soft Robotics and Users’ Associations with Them

Soft robotics provides flexible structures and materials that move in natural and organic ways. They facilitate creating safe and tolerant mechanisms for human–machine interaction. This makes soft robotics attractive for tasks that rigid robots are unable to carry out. Users may also display a higher acceptance of soft robots compared to rigid robots because their natural way of movement helps users to relate to scenarios they know from everyday life, making the interaction with the soft robot feel more intuitive. However, the variety of soft robotics shape designs, and how to integrate them into applications, have not been explored fully yet. In a user study, we investigated users’ associations and ideas for application areas for 36 soft robotics shape designs, brainstormed with users beforehand. We derived first design recommendations for soft robotics designs such as clear signifiers indicating the possible motion.