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2025 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2025

作者： Giovannelli, Alexander Murphy, Fionn Davis, Trey Lee, Chaerin Abulikemu, Rehema Gallagher, Matthew Sharma, Sahil Lisle, Lee Bowman, Doug A. Virginia Tech Center for Human-Computer Interaction Department of Computer Science BlacksburgVA United States

ISBN: (纸本)9798331514846

This paper presents our solution to the 2025 3DUI Contest challenge. We aimed to develop a collaborative, immersive experience that raises awareness about trash pollution in natural landscapes while enhancing traditional interaction techniques in virtual environments. To achieve these objectives, we created an engaging multiplayer game where one user collects harmful pollutants while the other user provides medication to impacted wildlife using enhancements to traditional interaction techniques: HOMER and Fishing Reel. We enhanced HOMER to use a cone volume to reduce the precise aiming required by a selection raycast to provide a more efficient means to collect pollutants at large distances, coined as FLOW-MATCH. To improve the animal feed distribution to wildlife far away from the user with Fishing Reel, we created RAWR-XD, an asymmetric bi-manual technique to more conveniently adjust the reeling speed using the non-selecting wrist rotation of the user. © 2025 IEEE.

关键词： Ambient intelligence

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BackTrace: A human-AI Collaborative Approach to Discovering Studio Backdrops in Historical Photographs 11th

BackTrace: A Human-AI Collaborative Approach to Discovering ...

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11th AAAI Conference on human Computation and Crowdsourcing, HCOMP 2023

作者： Lim, Jude Mohanty, Vikram Dodson, Terryl Luther, Kurt Center for Human-Computer Interaction and Department of Computer Science Virginia Tech United States

ISBN: (纸本)9781577358848

In historical photo research, the presence of painted backdrops have the potential to help identify subjects, photographers, locations, and events surrounding certain photographs. However, there are few dedicated tools or resources available to aid researchers in this largely manual task. In this paper, we propose BackTrace, a human-AI collaboration system that employs a three-step workfow to retrieve and organize historical photos with similar backdrops. BackTrace is a content-based image retrieval (CBIR) system powered by deep learning that allows for the iterative refnement of search results via user feedback. We evaluated BackTrace with mixed-methods evaluation and found that it successfully aided users in fnding photos with similar backdrops and grouping them into collections. Finally, we discuss how our fndings can be applied to other domains, as well as implications of deploying BackTrace as a crowdsourcing system. © 2023, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： Photography

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CoLT: Enhancing Collaborative Literature Review Tasks with Synchronous and Asynchronous Awareness Across the Reality-Virtuality Continuum

CoLT: Enhancing Collaborative Literature Review Tasks with S...

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2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct, ISMAR-Adjunct 2023

作者： Tahmid, Ibrahim A. Rodrigues, Francielly Giovannelli, Alexander Lisle, Lee Thomas, Jerald Bowman, Doug A. Virginia Tech Center for Human-Computer Interaction Department of Computer Science BlacksburgVA United States

ISBN: (纸本)9798350328912

Collaboration plays a vital role in both academia and industry whenever we need to browse through a big amount of data to extract meaningful insights. These collaborations often involve people living far from each other, with different levels of access to technology. Effective cross-border collaborations require reliable telepresence systems that provide support for communication, cooperation, and understanding of contextual cues. In the context of collaborative academic writing, while immersive technologies offer novel ways to enhance collaboration and enable efficient information exchange in a shared workspace, traditional devices such as laptops still offer better readability for longer articles. We propose the design of a hybrid cross-reality cross-device networked system that allows the users to harness the advantages of both worlds. Our system allows users to import documents from their personal computers (PC) to an immersive headset, facilitating document sharing and simultaneous collaboration with both colocated colleagues and remote colleagues. Our system also enables a user to seamlessly transition between Virtual Reality, Augmented Reality, and the traditional PC environment, all within a shared workspace. We present the real-world scenario of a global academic team conducting a comprehensive literature review, demonstrating its potential for enhancing cross-reality hybrid collaboration and productivity. © 2023 IEEE.

关键词： Augmented reality

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Exploring Multiscale Navigation of Homogeneous and Dense Objects with Progressive Refinement in Virtual Reality 32

Exploring Multiscale Navigation of Homogeneous and Dense Obj...

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32nd IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2025

作者： Pavanatto, Leonardo Giovannelli, Alexander Giera, Brian Bremer, Timo Miao, Haichao Bowman, Doug A. Virginia Tech Center for Human-Computer Interaction Department of Computer Science United States Lawrence Livermore National Laboratory Center for Applied Scientific Computing United States

ISBN: (纸本)9798331536459

Locating small features in a large, dense object in virtual reality (VR) poses a significant interaction challenge. While existing multiscale techniques support transitions between various levels of scale, they are not focused on handling dense, homogeneous objects with hidden features. We propose a novel approach that applies the concept of progressive refinement to VR navigation, enabling focused inspections. We conducted a user study where we varied two independent variables in our design, navigation style (STRUCTURED vs. UNSTRUCTURED) and display mode (SELECTION vs. EVERYTHING), to better understand their effects on efficiency and awareness during multiscale navigation. Our results showed that unstructured navigation can be faster than structured and that displaying only the selection can be faster than displaying the entire object. However, using an everything display mode can support better location awareness and object understanding. © 2025 IEEE.

关键词： Virtual reality

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Enhancing Immersive Sensemaking with Gaze-Driven Recommendation Cues 25

Enhancing Immersive Sensemaking with Gaze-Driven Recommendat...

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30th International Conference on Intelligent User Interfaces, IUI 2025

作者： Tahmid, Ibrahim Asadullah North, Chris Davidson, Kylie Whitley, Kirsten Bowman, Doug Computer Science Virginia Tech BlacksburgVA United States Department of Computer Science Virginia Tech BlacksburgVA United States Center for Human-Computer Interaction Virginia Tech BlacksburgVA United States Department of Defense College ParkMD United States

ISBN: (纸本)9798400713064

Sensemaking is a complex task that places a heavy cognitive demand on individuals. With the recent surge in data availability, making sense of vast amounts of information has become a significant challenge for many professionals, such as intelligence analysts. Immersive technologies such as mixed reality offer a potential solution by providing virtually unlimited space to organize data. However, the difficulty of processing, filtering relevant information, and synthesizing insights remains. We proposed using eye-tracking data from mixed reality head-worn displays to derive the analyst's perceived interest in documents and words, and convey that part of the mental model to the analyst. The global interest of the documents is reflected in their color, and their order on the list, while the local interest of the documents is used to generate focused recommendations for a document. To evaluate these recommendation cues, we conducted a user study with two conditions: a gaze-aware system, EyeST, and a "Freestyle"system without gaze-based visual cues. Our findings reveal that the EyeST helped analysts stay on track by reading more essential information while avoiding distractions. However, this came at the cost of reduced focused attention and perceived system performance. The results of our study highlight the need for explainable AI in human-AI collaborative sensemaking to build user trust and encourage the integration of AI outputs into the immersive sensemaking process. Based on our findings, we offer a set of guidelines for designing gaze-driven recommendation cues in an immersive environment. © 2025 Copyright held by the owner/author(s).

关键词： Information filtering

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Exploring Effect of Level of Storytelling Richness on science Learning in Interactive and Immersive Virtual Reality 22

Exploring Effect of Level of Storytelling Richness on Scienc...

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2022 ACM International Conference on Interactive Media Experiences, IMX 2022

作者： Zhang, Lei A. Bowman, Doug Human-Centered Design Virginia Tech United States Center for Human Computer Interaction Virginia Tech Computer Science United States

ISBN: (纸本)9781450392129

Immersive and interactive storytelling in virtual reality (VR) is an emerging creative practice that has been thriving in recent years. Educational applications using immersive VR storytelling to explain complex science concepts have very promising pedagogical benefits because on the one hand, storytelling breaks down the complexity of science concepts by bridging them to people's everyday experiences and familiar cognitive models, and on the other hand, the learning process is further reinforced through rich interactivity afforded by the VR experiences. However, it is unclear how different amounts of storytelling in an interactive VR storytelling experience may affect learning outcomes due to a paucity of literature on educational VR storytelling research. This preliminary study aims to add to the literature through an exploration of variations in the designs of essential storytelling elements in educational VR storytelling experiences and their impact on the learning of complex immunology concepts. © 2022 ACM.

关键词： Virtual reality

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What Lies Beneath? Exploring the Impact of Underlying AI Model Updates in AI-Infused Systems 25

What Lies Beneath? Exploring the Impact of Underlying AI Mod...

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2025 CHI Conference on human Factors in Computing Systems, CHI 2025

作者： Mohanty, Vikram Lim, Jude Luther, Kurt Human-Computer Interaction Institute Carnegie Mellon University PittsburghPA United States Independent Researcher ArlingtonVA United States Department of Computer Science Center for Human-Computer Interaction Virginia Tech AlexandriaVA United States

ISBN: (纸本)9798400713941

AI models are constantly evolving, with new versions released frequently. human-AI interaction guidelines encourage notifying users about changes in model capabilities, ideally supported by thorough benchmarking. However, as AI systems integrate into domain-specific workflows, exhaustive benchmarking can become impractical, often resulting in silent or minimally communicated updates. This raises critical questions: Can users notice these updates? What cues do they rely on to distinguish between models? How do such changes affect their behavior and task performance? We address these questions through two studies in the context of facial recognition for historical photo identification: an online experiment examining users' ability to detect model updates, followed by a diary study exploring perceptions in a real-world deployment. Our findings highlight challenges in noticing AI model updates, their impact on downstream user behavior and performance, and how they lead users to develop divergent folk theories. Drawing on these insights, we discuss strategies for effectively communicating model updates in AI-infused systems. © 2025 Copyright held by the owner/author(s).

关键词： AI Model Updates

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Virtual Displays for Knowledge Work: Extending or Replacing Physical Monitors for More Flexibility and Screen Space

Virtual Displays for Knowledge Work: Extending or Replacing ...

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Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), IEEE Conference on

作者： Leonardo Pavanatto Doug A. Bowman Department of Computer Science Center for Human-Computer Interaction Virginia Tech USA

ISBN: (数字)9798350374490

ISBN: (纸本)9798350374506

In this paper, we explore the potential of virtual displays in sup-porting knowledge work, focusing on scenarios where conventional physical monitors fall short. Our research investigates the feasibility and productivity costs of extending or replacing physical monitors with augmented and virtual reality displays. We present three com-pelling use cases, illustrating how virtual displays enhance flexibility, adaptability, and customization in remote and diverse work settings. Lessons learned from user studies highlight hardware and interface design challenges, emphasizing the need for larger resolution and field of view in head-worn displays (HWD). We conclude the paper with research opportunities and a call to address the evolving demands of knowledge work interfaces.

关键词： Productivity Three-dimensional displays Head-mounted displays Focusing Virtual reality User interfaces Hardware

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Planet Purifiers: A Collaborative Immersive Experience Proposing New Modifications to HOMER and Fishing Reel interaction techniques

Planet Purifiers: A Collaborative Immersive Experience Propo...

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Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), IEEE Conference on

作者： Alexander Giovannelli Fionn Murphy Trey Davis Chaerin Lee Rehema Abulikemu Matthew Gallagher Sahil Sharma Lee Lisle Doug A. Bowman Department of Computer Science Center for Human-Computer Interaction Virginia Tech Blacksburg VA USA

ISBN: (数字)9798331514846

ISBN: (纸本)9798331525637

关键词： Wrist Three-dimensional displays Pollution Planets Wildlife Collaboration Virtual environments Immersive experience Games Food products

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CrowdSolve: Managing Tensions in an Expert-Led Crowdsourced Investigation

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Proceedings of the ACM on human-computer interaction 2021年第CSCW1期5卷 1-30页

作者： Venkatagiri, Sukrit Gautam, Aakash Luther, Kurt Department Of Computer Science Center For Human-Computer Interaction Virginia Tech-1 ArlingtonVA United States

Investigators in fields such as journalism and law enforcement have long sought the public's help with investigations. New technologies have also allowed amateur sleuths to lead their own crowdsourced investigations-that have traditionally only been the purview of expert investigators-with mixed results. Through an ethnographic study of a four-day, co-located event with over 250 attendees, we examine the human infrastructure responsible for enabling the success of an expert-led crowdsourced investigation. We find that the experts enabled attendees to generate useful leads;the attendees formed a community around the event;and the victims' families felt supported. Additionally, the co-located setting, legal structures, and emergent social norms impacted collaborative work practice. We also surface three important tensions to consider in future investigations and provide design recommendations to manage these tensions. © 2021 ACM.

关键词： Crowdsourcing

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