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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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Multidimensional image morphing-fast image-based rendering of open 3D and VR environments

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虚拟现实与智能硬件(中英文) 2025年第2期7卷 155-172页

作者： Simon SEIBT Bastian KUTH Bartosz von Rymon LIPINSKI Thomas CHANG Marc Erich LATOSCHIK Game Tech Laboratory Faculty of Computer ScienceNuremberg Institute of TechnologyNuremberg 90489Germany Department of Electrical Engineering and Computer Science Coburg University of Applied Sciences and ArtsCoburg 96450Germany Human-Computer Interaction Group Institute of Computer ScienceUniversity of WuerzburgWuerzburg 97074Germany

Background In recent years,the demand for interactive photorealistic three-dimensional(3D)environments has increased in various fields,including architecture,engineering,and ***,achieving a balance between the quality and efficiency of high-performance 3D applications and virtual reality(VR)remains *** This study addresses this issue by revisiting and extending view interpolation for image-based rendering(IBR),which enables the exploration of spacious open environments in 3D and ***,we introduce multimorphing,a novel rendering method based on the spatial data structure of 2D image patches,called the image *** this approach,novel views can be rendered with up to six degrees of freedom using only a sparse set of *** rendering process does not require 3D reconstruction of the geometry or per-pixel depth information,and all relevant data for the output are extracted from the local morphing cells of the image *** detection of parallax image regions during preprocessing reduces rendering artifacts by extrapolating image patches from adjacent cells in *** addition,a GPU-based solution was presented to resolve exposure inconsistencies within a dataset,enabling seamless transitions of brightness when moving between areas with varying light *** Experiments on multiple real-world and synthetic scenes demonstrate that the presented method achieves high"VR-compatible"frame rates,even on mid-range and legacy hardware,*** achieving adequate visual quality even for sparse datasets,it outperforms other IBR and current neural rendering *** Using the correspondence-based decomposition of input images into morphing cells of 2D image patches,multidimensional image morphing provides high-performance novel view generation,supporting open 3D and VR ***,the handling of morphing artifacts in the parallax image regions remains a topic for future resea

关键词： computer graphics 3D real-time rendering computer vision Image morphing Virtual reality

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Pseudo-Haptics for Weight Perception in VR: Controller vs. Bare Hand interactions with Tracking Delay and Vertical Offset 10

Pseudo-Haptics for Weight Perception in VR: Controller vs. B...

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10th International Conference on Virtual Reality, ICVR 2024

作者： Hwang, Chiwoong Feuchtner, Tiare Gronbak, Kaj Aarhus University Department of Computer Science Denmark Konstanz University Human-Computer Interaction Group Germany

ISBN: (纸本)9798350364231

Training in virtual reality (VR) offers advantages such as a safe learning environment, good scalability, and cost saving. However, state-of-the-art simulations are limited in faithfully conveying real-world physical object properties such as weight without complex technologies and instrumentation of the user or environment, which may negatively impact learning. A potential solution is the application of pseudo-haptics: illusory haptic sensations induced by a mismatch between real and virtual hand positions. Researchers have proposed various pseudo-haptic techniques to alter the perception of weight in virtual environments, but their effectiveness with hand tracking compared to VR controllers is underexplored. Hence, we investigate impacts of the interaction method for two different types of pseudo-haptic feedback based on Tracking Delay and Vertical Offset. Our results indicate that pseudo-haptics can effectively facilitate the sensation of weight both with controllers and bare hands, whereby each has benefits: hand tracking can enhance body ownership, while controllers may improve perceived responsiveness of virtual environments. Also, pseudo-haptics with Tracking Delay may be preferable for repetitive lifting tasks, as Vertical Offset can be prone to higher physical demand. The current study provides insights into the design of pseudo-haptic feedback and interaction technologies for weight perception in VR. © 2024 IEEE.

关键词： Virtual environments

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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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A unified user behavior model for trajectory-based tasks with different types of path constraints

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science China(Information sciences) 2023年第10期66卷 316-318页

作者： Hao ZHANG Jin HUANG Huawei TU Feng TIAN Guozhong DAI Hongan WANG Beijing Key Laboratory of Human-Computer Interaction Institute of Software Chinese Academy of Sciences School of Computer Science and Technology University of Chinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences Department of Computer Science and Information Technology La Trobe University

An important research branch of human-computer interaction(HCI) is to develop predictive models for human performance in fundamental interactions [1]. On today's graphical user interface(GUI), users often implicitly perform various trajectory-based interactions, such as navigating through menus [2], entering the boundary of a button,

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Digital Shadows: Exploring the Other and the I in Communication with Thanabots 6

Digital Shadows: Exploring the Other and the I in Communicat...

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6th Social Robots with AI: Prospects, Risks, and Responsible Methods Robophilosophy, RP 2024

作者： Dobrosovestnova, Anna Machado, Felipe Reinboth, Tim Human Computer Interaction Group TU Wien Austria Department of Philosophy Cognitive Science Hub University of Vienna Austria

ISBN: (纸本)9781643685670

The development of large language models (LLMs) has led to the proliferation of chatbot services like ChatGPT, Replika and Project December further contributing to technologically mediated grief. Called variously griefbots, or thanabots, the postulated aim behind these technologies is to help people deal with the loss of their loved ones. Despite hype around these technologies in the media, little is still known about the actual mechanisms of how thanabots contribute to grieving. This paper contributes to answering this question by offering an interpretation of communication with thanabots through the prism of Yuri Lotman's autocommunication model. We start by examining how a thanabot can be framed as a communicational 'other'. Then we draw on phenomenology of grief literature to delineate the boundaries of such "otherness". In line with the Lotman's autocommunication model, we proceed to argue that conversing with a thanabot can be viewed as an instance of 'I-I' communication. Within this model, the bot functions as a secondary code that allows for new meaning to arise in the process of communication and, consequently, for a bereaved person to renegotiate their new identity in the face of loss. © 2025 IOS Press. All rights reserved.

关键词： I-I I-Other Large Language Models phenomenology of grief thanabots

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Unlocking the potential of public opinions for niche development using acceptance mining

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Methodological Innovations 2023年第1期16卷 78-90页

作者： Digmayer, Claas Jakobs, Eva-Maria Department of Textlinguistics and Technical Communication Human-Computer Interaction Center RWTH Aachen University Aachen Germany

This paper proposes a combination of text mining and acceptance research as a methodological approach (“acceptance mining”) to facilitate the development of innovative technologies in niches. At the example of recharging infrastructures for electric vehicles, the approach is explored on a sample of over 20,000 user comments collected from social media and discussion forums. The results indicate that acceptance mining provides valuable insights into the demands of the public during all phases of niche development which allow shaping niches in socially acceptable ways. In particular, the method reveals requirements and risks of niche-development measures such as shielding, nurturing, and empowering niches as perceived by the public. The results are discussed regarding the potentials of acceptance mining for developing innovations in niches as well as its limitations and possibilities for optimization. Acceptance mining and its application to a case study are especially of interest for researchers and practitioners involved in niche development;the study results provide valuable insights for professionals engaged in developing recharging infrastructures for electric vehicles. © The Author(s) 2023.

关键词： Acceptance mining combination of quantitative and qualitative methods development of technological innovations in niches social acceptance of niche development technology development text mining

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A Corpus and Method for Chinese Named Entity Recognition in Manufacturing 30

A Corpus and Method for Chinese Named Entity Recognition in ...

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Li, Ruiting Wang, Peiyan Wang, Libang Yang, Danqingxin Cai, Dongfeng School of Computer Science Shenyang Aerospace University Shenyang China Liaoning Professional Technology Innovation Center on Knowledge Engineering and Human-Computer Interaction Shenyang China

ISBN: (纸本)9782493814104

Manufacturing specifications are documents entailing different techniques, processes, and components involved in manufacturing. There is a growing demand for named entity recognition (NER) resources and techniques for manufacturing-specific named entities, with the development of smart manufacturing. In this paper, we introduce a corpus of Chinese manufacturing specifications, named MS-NERC, including 4,424 sentences and 16,383 entities. We also propose an entity recognizer named Trainable State Transducer (TST), which is initialized with a finite state transducer describing the morphological patterns of entities. It can directly recognize entities based on prior morphological knowledge without training. Experimental results show that TST achieves an overall 82.05% F1 score for morphological-specific entities in zero-shot. TST can be improved through training, the result of which outperforms neural methods in few-shot and rich-resource. We believe that our corpus and model will be valuable resources for NER research not only in manufacturing but also in other low-resource domains. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Transducers

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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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