具有重定向行走的全沉浸式多用户虚拟现实用户移动模拟器

Filip Lemic, Jakob Struye, J. Famaey
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引用次数: 2

摘要

全沉浸式多用户虚拟现实(VR)设备设想支持虚拟世界中VR用户的无缝移动,同时通过重定向行走将他们限制在共享的物理空间内。为了在这种设置中实现高数据速率和低延迟的视频内容传输,支持的无线网络必须利用高度定向的通信链路,这些链路将理想地“跟踪”移动VR用户,以保持视线(LoS)连接。因此,关于虚拟世界中VR用户的移动性模式的设计决策将对这些用户在物理环境中的移动性产生重大影响,因此也会对底层网络的性能产生重大影响。因此,需要一种工具,它可以提供关于用户在虚拟单词中的移动性的设计决策之间的映射,以及它们对受限物理设置中的移动性的影响。为了解决这个问题,我们开发了一个模拟器来实现这个功能。给定一组VR用户的虚拟运动轨迹,物理部署环境的轮廓,以及避免物理碰撞的重定向行走算法,模拟器能够推导出用户的物理运动。基于派生的物理运动,模拟器可以捕获一组性能指标,表征可感知重置的数量以及每个用户的重置之间的距离。模拟器还能够显示物理运动轨迹的可预测性,这可以作为底层网络支持给定虚拟运动模式的复杂性的指示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
User Mobility Simulator for Full-Immersive Multiuser Virtual Reality with Redirected Walking
Full-immersive multiuser Virtual Reality (VR) setups envision supporting seamless mobility of the VR users in the virtual worlds, while simultaneously constraining them inside shared physical spaces through redirected walking. For enabling high data rate and low latency delivery of video content in such setups, the supporting wireless networks will have to utilize highly directional communication links, where these links will ideally have to “track” the mobile VR users for maintaining the Line-of-Sight (LoS) connectivity. The design decisions about the mobility patterns of the VR users in the virtual worlds will thus have a substantial effect on the mobility of these users in the physical environments, and therefore also on performance of the underlying networks. Hence, there is a need for a tool that can provide a mapping between design decisions about the users' mobility in the virtual words, and their effects on the mobility in constrained physical setups. To address this issue, we have developed and in this paper present a simulator for enabling this functionality. Given a set of VR users with their virtual movement trajectories, the outline of the physical deployment environment, and a redirected walking algorithm for avoiding physical collisions, the simulator is able to derive the physical movements of the users. Based on the derived physical movements, the simulator can capture a set of performance metrics characterizing the number of perceivable resets and the distances between such resets for each user. The simulator is also able to indicate the predictability of the physical movement trajectories, which can serve as an indication of the complexity of supporting a given virtual movement pattern by the underlying networks.
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