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IEEE Conference on Virtual Reality and 3D User Interfaces (IEEE VR)

作者： Martinez, Esteban Segarra Wu, Annie S. McMahan, Ryan P. Univ Cent Florida Dept Comp Sci Orlando FL 32816 USA

ISBN: (纸本)9781665496179

Virtual reality (VR) researchers have had a long-standing interest in studying locomotion for developing new techniques, improving upon prior ones, and analyzing their effects on users. To help organize prior work, several researchers have presented taxonomies for categorizing locomotion techniques in general. More recently, researchers have begun to conduct systematic reviews to better understand what locomotion techniques have been investigated. In this paper, we present our own systematic review of locomotion techniques based on a well-established taxonomy, and we use k-means clustering to identify to what extent locomotion techniques have been explored. Our results indicate that selection-based, walking-based, and steering-based locomotion techniques have been moderately to highly explored while manipulation-based and automated locomotion techniques have been less explored. We also present results on what types of metrics have been used to evaluate locomotion techniques. While usability, discomfort, and travel performance metrics have been moderately to highly explored, other metrics, such as biometrics, user experience, and emotions, have been less explored.

关键词： human-centered computing human computer interaction (HCI) Interaction paradigms Virtual reality

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A hybrid quantum-classical conditional generative adversarial network algorithm for human-centered paradigm in cloud

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EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING 2021年第1期2021卷 1-17页

作者： Liu, Wenjie Zhang, Ying Deng, Zhiliang Zhao, Jiaojiao Tong, Lian Nanjing Univ Informat Sci & Technol Sch Comp & Software Nanjing 210044 Peoples R China Minist Educ Engn Res Ctr Digital Forens Nanjing 210044 Peoples R China Nanjing Univ Informat Sci & Technol Sch Automat Nanjing 210044 Peoples R China Jiangsu Maritime Inst Sch Informat Engn Nanjing 211100 Peoples R China

As an emerging field that aims to bridge the gap between human activities and computing systems, human-centered computing (HCC) in cloud, edge, fog has had a huge impact on the artificial intelligence algorithms. The quantum generative adversarial network (QGAN) is considered to be one of the quantum machine learning algorithms with great application prospects, which also should be improved to conform to the human-centered paradigm. The generation process of QGAN is relatively random and the generated model does not conform to the human-centered concept, so it is not quite suitable for real scenarios. In order to solve these problems, a hybrid quantum-classical conditional generative adversarial network (QCGAN) algorithm is proposed, which is a knowledge-driven human-computer interaction computing mode that can be implemented in cloud. The purposes of stabilizing the generation process and realizing the interaction between human and computing process are achieved by inputting artificial conditional information in the generator and discriminator. The generator uses the parameterized quantum circuit with an all-to-all connected topology, which facilitates the tuning of network parameters during the training process. The discriminator uses the classical neural network, which effectively avoids the "input bottleneck" of quantum machine learning. Finally, the BAS training set is selected to conduct experiment on the quantum cloud computing platform. The result shows that the QCGAN algorithm can effectively converge to the Nash equilibrium point after training and perform human-centered classification generation tasks.

关键词： Quantum generative adversarial network Conditional generative adversarial network human-centered computing Cloud computing Parameterized quantum circuits

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A Live-Coded Add-On System for Video Conferencing in Virtual Reality

A Live-Coded Add-On System for Video Conferencing in Virtual...

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IEEE Conference on Virtual Reality and 3D User Interfaces (IEEE VR)

作者： Razi, Septian Gardner, Henry Sorensen, Andrew Adcock, Matt Australian Natl Univ Canberra ACT Australia MOSO Corp Brisbane Qld Australia CSIROs Data61 Sydney NSW Australia

ISBN: (纸本)9781665484022

Despite our increasing reliance on video conferencing, it has inherent limitations in engagement and effective communication. We explore a VR add-on system that supplements traditional video conferencing where a host live-codes data visualisations for stakeholders. It combines VR visualisation techniques with libraries present in popular data analytics tools such as Python, allowing real-time changes by utilising a RESTful realtime database. An application has been built to explore pedigree node-link graphs, and its feasibility has been analysed with a few domain experts. Trials have demonstrated that our system appears to enhance engagement and communication above traditional video conferencing for data exploration.

关键词： human-centered computing Visualization Visualization techniques Graph drawings human-centered computing Visualization Visualization application domains Scientific visualization human-centered computing human computer interaction (HCI) Interaction paradigms Virtual reality

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On Eliminating Blocking Interference of RFID Unauthorized Reader Detection 17th

On Eliminating Blocking Interference of RFID Unauthorized Re...

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17th International Conference on Wireless Algorithms, Systems, and Applications (WASA)

作者： Sun, Degang Cui, Yue Wang, Siye Zhang, Yanfang Chinese Acad Sci Inst Informat Engn Beijing Peoples R China Univ Chinese Acad Sci Sch Cyber Secur Beijing Peoples R China

ISBN: (纸本)9783031192074;9783031192081

RFID as an important component technology of IoT is rapidly applied in recent years. But it also faces severe security risks like malicious intrusion, most operated by unauthorized reader (UR). There are some researches proposed the unauthorized reader detection algorithms based on commercial off-the-shelf (COTS) devices, but these detection algorithms are often easily affected by moving objects blocking interference, causing false alarms. We adopt a new parameter adjacent signals time interval (ASTI) to improve the UR detection algorithm by reducing the time-delay and propose a new method of eliminating moving object interference, which can reduce the system false alarm rate to less than 7.9% by experimental testing.

关键词： RFID security Intrusion detection human-centered computing Privacy protection

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Virtual Workspace Positioning Techniques during Teleportation for Co-located Collaboration in Virtual Reality using HMDs 29

Virtual Workspace Positioning Techniques during Teleportatio...

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IEEE Conference on Virtual Reality and 3D User Interfaces (IEEE VR)

作者： Zhang, Yiran Nguyen, Huyen Ladeveze, Nicolas Fleury, Cedric Bourdot, Patrick Univ Paris Saclay CNRS LISN VENISE Team Orsay France Univ Paris Saclay LISN VENISE Team Orsay France IMT Atlantique Lab STICC UMR CNRS 6285 Brest France

ISBN: (纸本)9781665496179

In many collaborative virtual reality applications, co-located users often have their relative position in the virtual environment matching the one in the real world. The resulting spatial consistency facilitates the co-manipulation of shared tangible props and enables the users to have direct physical contact with each other. However, these applications usually exclude their individual virtual navigation capability, such as teleportation, as it may break the spatial configuration between the real and virtual world. As a result, the users can only explore the virtual environment of approximately similar size and shape compared to their physical workspace. Moreover, their individual tasks with unlimited virtual navigation capability, which often take part in a continuous workflow of a complex collaborative scenario, have to be removed due to this constraint. This work aims to help overcome these limits by allowing users to recover spatial consistency after individual teleportation in order to re-establish their position in the current context of the collaborative task. We use a virtual representation of the user's shared physical workspace and develop two different techniques to position it in the virtual environment. The first technique allows one user to fully position the virtual workspace, and the second approach enables concurrent positioning by equally integrating the input from all the users. We compared these two techniques in a controlled experiment in a virtual assembly task. The results show that allowing two users to manipulate the workspace significantly reduced the time they spent negotiating the position of the future workspace. However, the inevitable conflicts in simultaneous co-manipulation were also a little confusing to them.

关键词： human-centered computing human computer interaction (HCI) Interaction paradigms Virtual reality human-centered computing human computer interaction (HCI) Interaction paradigms Collaborative interaction

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An Interdisciplinary Perspective on Evaluation and Experimental Design for Visual Text Analytics: Position Paper 9

An Interdisciplinary Perspective on Evaluation and Experimen...

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9th IEEE Evaluation and Beyond - Methodological Approaches for Visualization (BELIV)

作者： Kucher, Kostiantyn Sultanum, Nicole Daza, Angel Simaki, Vasiliki Skeppstedt, Maria Plank, Barbara Fekete, Jean-Daniel Mahyar, Narges Linkoping Univ Linkoping Sweden Linnaeus Univ Vaxjo Sweden Univ Toronto Toronto ON Canada Vrije Univ Amsterdam Amsterdam Netherlands Lund Univ Lund Sweden Uppsala Univ Dept ALM CDHU Uppsala Sweden Ludwig Maximilians Univ Munchen IT Univ Copenhagen Munich Germany Univ Paris Saclay INRIA Paris France UMass Amherst Amherst MA USA

ISBN: (数字)9798350396294

ISBN: (纸本)9798350396294

Appropriate evaluation and experimental design are fundamental for empirical sciences, particularly in data-driven fields. Due to the successes in computational modeling of languages, for instance, research outcomes are having an increasingly immediate impact on end users. As the gap in adoption by end users decreases, the need increases to ensure that tools and models developed by the research communities and practitioners are reliable, trustworthy, and supportive of the users in their goals. In this position paper, we focus on the issues of evaluating visual text analytics approaches. We take an interdisciplinary perspective from the visualization and natural language processing communities, as we argue that the design and validation of visual text analytics include concerns beyond computational or visual/interactive methods on their own. We identify four key groups of challenges for evaluating visual text analytics approaches (data ambiguity, experimental design, user trust, and "big picture" concerns) and provide suggestions for research opportunities from an interdisciplinary perspective.

关键词： human-centered computing Visualization Visualization design and evaluation methods

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Context-Aware Inference and Adaptation in Augmented Reality

Context-Aware Inference and Adaptation in Augmented Reality

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IEEE Conference on Virtual Reality and 3D User Interfaces (IEEE VR)

作者： Davari, Shakiba Virginia Tech Ctr Human Comp Interact Blacksburg VA 24061 USA Virginia Tech Dept Comp Sci Blacksburg VA 24061 USA

ISBN: (纸本)9781665484022

Augmented Reality(AR) offers the potential for easy and efficient information access, reinforcing the wide belief that AR Glasses are the next-generation of personal computing devices. However, to realize this all-day AR vision, the AR interface must be able to address the challenges that constant and pervasive presence of virtual content can cause for the user. The optimal interface, that is the most efficient yet least intrusive, in one context may be the worst interface for another context. Throughout the day, as the user switches context, an optimal all-day interface must adapts its virtual content display and interactions as well. This work aims to propose a research agenda to design and validate different adaptation techniques and context-aware AR interfaces and introduce a framework for the design of such intelligent interfaces.

关键词： human-centered computing Mixed / augmented reality human-centered computing Interaction techniques human-centered computing Empirical Studies in HCI

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Whac-A-Mole: Exploring Virtual Reality (VR) for Upper-Limb Post -Stroke Physical Rehabilitation based on Participatory Design and Serious Games

Whac-A-Mole: Exploring Virtual Reality (VR) for Upper-Limb P...

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IEEE Conference on Virtual Reality and 3D User Interfaces (IEEE VR)

作者： Paraense, Helder Marques, Bernardo Amorim, Paula Dias, Paulo Santos, Beatriz Sousa Univ Aveiro DETI IEETA Aveiro Portugal Univ Beira Interior FCS Covilha Portugal

ISBN: (纸本)9781665484022

This paper describes a human-centered Design process aimed at understanding how Virtual Reality (VR) can assist in post-stroke physical rehabilitation. Based on insights from stroke survivors and healthcare professionals, a serious game prototype is proposed. We focused on upper-limb rehabilitation, which inspired the game narrative and the movements users must perform. The game supports two modes: 1- normal version - users can use any arm to pick a virtual hammer and hit objects;2- mirror version - converts a traditional approach to VR, providing the illusion that the arm affected by the stroke is moving. These were evaluated through a user study.

关键词： human-centered computing human computer interaction (HCI) Interaction Paradigms Mixed/augmented reality human-centered computing human computer interaction (HCI) HCI Design and Evalution Methods UserStudies

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QoE Study of Natural Interaction in Extended Reality Environment for Immersive Training

QoE Study of Natural Interaction in Extended Reality Environ...

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IEEE Conference on Virtual Reality and 3D User Interfaces (IEEE VR)

作者： Cortes, Carlos Rubio, Maria Perez, Pablo Sanchez, Beatriz Garcia, Narciso Univ Politecn Madrid Madrid Spain Nokia TECSS Madrid Spain Nokia Bell Labs Holmdel NJ USA Nokia Espoo Finland

ISBN: (纸本)9781665484022

Immersive training is a hot topic in areas like construction. However, most of the implemented use cases require external tools to allow interaction. This can lead to an immersive uprooting of user experience. In this paper we present a use case of immersive training using natural interfaces for interaction in construction, which has been tested by professionals working in construction of fiber networks and evaluated in terms of quality, presence and sickness to validate its impact on immersion.

关键词： human-centered computing human computer interaction Extended reality Mixed Reality Natural Interfaces Immersive Learning human-centered computing Virtual Reality Quality of Experience Visualization design and evaluation methods

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Exploring Efficiency of Vision Transformers for Self-Supervised Monocular Depth Estimation 21

Exploring Efficiency of Vision Transformers for Self-Supervi...

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21st IEEE International Symposium on Mixed and Augmented Reality (ISMAR)

作者： Karpov, Aleksei Makarov, Ilya AIRI Moscow Russia HSE Univ Moscow Russia Docet TI Tel Aviv Israel

ISBN: (数字)9781665453257

ISBN: (纸本)9781665453257

Depth estimation is a crucial task for the creation of depth maps, one of the most important components for augmented reality (AR) and other applications. However, the most widely used hardware for AR and smartphones has only sparse depth sensors with different ground truth depth acquisition methods. Thus, depth estimation models that are robust for downstream AR tasks performance can only be trained reliably using self-supervised learning based on camera information. Previous works in the field mostly focus on self-supervised models with pure convolutional architectures, without taking global spatial context into account. In this paper, we utilize vision transformer architectures for self-supervised monocular depth estimation and propose VTDepth, a vision transformer-based model, which provides a solution to the problem of the global spatial context. We compare various combinations of convolutional and transformer architectures for self-supervised depth estimation and show that the best combination of models is an encoder with a transformer basis and convolutional decoder. Our experiments demonstrate the efficiency of VTDepth for self-supervised depth estimation. Our set of models achieves state-of-the-art performance for self-supervised learning on NYUv2 and KITTI datasets. Our code is available at https://***/ahbpp/VTDepth.

关键词： human-centered computing human computer interaction (HCI) Interaction paradigms Mixed / augmented reality Artificial intelligence Computer vision Localization, spatial registration and tracking 3D reconstruction

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