HCC: Small: Making Virtual Reality Safe

HCC：小型：确保虚拟现实安全

• 批准号: 2316240
• 负责人: John Quarles
• 金额: $ 60万
• 依托单位: University of Texas at San Antonio
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-01-01 至 2026-12-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2316240&HistoricalAwards=false
• 关键词: HCC; Small; Making; Virtual; Reality

Although consumer-level virtual reality head-mounted displays have become affordable enough for a broad user base to purchase, there are still serious concerns about safety. Head-mounted displays block out the surrounding real world, which can hide obstacles, such as tables, pets, walls, or other potential collision hazards. Current approaches to avoiding collisions depend on the user to define play area boundaries; this process is subject to user error and thus can lead to injury. Moreover, current approaches are ineffective for games that require fast motions, as the systems may not react in time to prevent injury. To address these problems, the investigators will create camera-based methods for detecting potential collisions in real time and evaluate feedback techniques to reduce the incidence of injury when using virtual reality headsets. This approach has the potential to make the use of virtual reality much safer in real-world environments.The objective of this project is to create and evaluate reconstruction, segmentation, and motion-prediction techniques to inform obstacle avoidance feedback and reduce the incidence of injury to people using virtual reality head mounted displays. Providing feedback tailored to the specific locations of the user's body that are in proximity to real obstacles will, ideally, reduce user collisions with real-world objects compared to prior approaches. Specifically, the team will 1) determine the best approaches to real obstacle detection and segmentation, 2) investigate the efficacy of full body motion prediction approaches, 3) ascertain the optimal modality and locations of real obstacle alerts to maximize presence while minimizing collisions, and 4) evaluate the longitudinal impact of real obstacle alert systems in virtual reality systems. Ultimately, this research will result in human motion datasets that can be used for future motion prediction in virtual reality research, as well as open-source plugins that will make current virtual reality experiences safer by reducing injuries.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

尽管消费者级的虚拟现实头部安装的显示器已经足够负担得起，可以购买广泛的用户群，但仍然对安全有严重的担忧。头戴式显示器阻止了周围的现实世界，该世界可能会隐藏障碍物，例如桌子，宠物，墙壁或其他潜在的碰撞危险。避免碰撞的当前方法取决于用户定义游戏区域边界；此过程可能会出现用户错误，因此可能导致受伤。此外，目前的方法对于需要快速动作的游戏无效，因为系统可能不会及时做出反应以防止伤害。为了解决这些问题，研究人员将创建基于摄像机的方法，以实时检测潜在的冲突，并评估反馈技术以减少使用虚拟现实耳机时受伤的发生率。这种方法有可能使虚拟现实在现实环境中更加安全。该项目的目的是创建和评估重建，细分和运动预测技术，以告知避免障碍的反馈，并减少使用虚拟现实头架显示的人的受伤发生率。提供针对用户身体特定位置量身定制的反馈，与先前的方法相比，理想情况下，将减少用用户与现实世界对象的碰撞。具体而言，团队将1）确定真正的障碍检测和细分的最佳方法，2）研究全身运动预测方法的功效，3）确定真正的障碍警报的最佳方式和最大化碰撞的实际障碍警报的位置，同时最大程度地减少碰撞，4）评估实际障碍警报系统对虚拟销售系统的纵向影响。最终，这项研究将导致人类运动数据集可用于虚拟现实研究中的未来运动预测，以及开源插件，这些插件将通过减少伤害来使当前的虚拟现实体验更加安全。该奖项反映了NSF的法定任务，并通过使用该基金会的知识优点和广泛的影响来评估NSF的法定任务。