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在手部消失之前:虚拟现实中手部跟踪失败的早期预警视觉反馈方法的效果

Before hands disappear: Effect of early warning visual feedback method for hand tracking failures in virtual reality.

作者信息

Gemici Mucahit, Phadnis Vrushank, Batmaz Anil Ufuk

机构信息

Department of Computer Science & Software Engineering, Concordia University, Montreal, Quebec, Canada.

Google, Mountain View, California, United States of America.

出版信息

PLoS One. 2025 Jun 10;20(6):e0323796. doi: 10.1371/journal.pone.0323796. eCollection 2025.

Abstract

Virtual hand representation in Head-Mounted Displays (HMDs) offers immersive and intuitive interactions in Virtual Reality (VR). However, current hand tracking algorithms are prone to errors, which can disrupt the user experience and hinder task performance. This paper presents a novel method for providing users with visual feedback when the quality of hand tracking decreases. Our approach employs a notification modal that warns users of potential failures. We identified three common hand tracking failure scenarios and evaluated the effectiveness of our method in two distinct VR tasks: object manipulation and complex assembly tasks. Results show that our early warning system reduces task completion time, lowers hand-tracking failures by up to 83%, decreases errors, improves system usability, and reduces cognitive load. This work contributes to the development of more robust and user-friendly VR HMD applications by enhancing hand tracking reliability, usability, and workload.

摘要

头戴式显示器(HMD)中的虚拟手部呈现为虚拟现实(VR)提供了沉浸式和直观的交互体验。然而,当前的手部跟踪算法容易出错,这可能会破坏用户体验并阻碍任务执行。本文提出了一种在手部跟踪质量下降时为用户提供视觉反馈的新方法。我们的方法采用了一种通知模式,警告用户潜在的失败情况。我们识别了三种常见的手部跟踪失败场景,并在两个不同的VR任务中评估了我们方法的有效性:物体操纵和复杂装配任务。结果表明,我们的预警系统减少了任务完成时间,将手部跟踪失败率降低了高达83%,减少了错误,提高了系统可用性,并降低了认知负荷。这项工作通过提高手部跟踪的可靠性、可用性和工作量,为更强大、更用户友好的VR HMD应用程序的开发做出了贡献。

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