论文标题
部分可观测时空混沌系统的无模型预测
Multi-User Redirected Walking in Separate Physical Spaces for Online VR Scenarios
论文作者
论文摘要
随着元元的近期增长,在线多人VR应用程序在全球范围内变得越来越普遍。允许用户在虚拟环境中轻松移动对于此类协作VR应用程序中的高质量体验至关重要。本文着重于重定向的步行技术(RDW),以使用户超越有限的物理环境(PE)的范围。现有的RDW方法缺乏协调不同PE的多个用户的方案,因此存在触发太多重置的问题。我们提出了一种新型的多用户RDW方法,能够通过提供更连续的探索来显着减少总体复位数,并为用户提供更好的沉浸式体验。我们的关键想法是首先找出可能导致所有用户重置并估算重置时间的“瓶颈”用户,然后在最大的瓶颈时间中将所有用户重新定向为有利的姿势,以确保可以尽可能多地将其重置。更特别地,我们开发了估计可能遇到障碍的时间的方法,以及特定姿势的可到达区域,以实现任何用户引起的下一个重置的预测。我们的实验和用户研究发现,我们的方法在在线VR应用程序中优于现有的RDW方法。
With the recent rise of Metaverse, online multiplayer VR applications are becoming increasingly prevalent worldwide. Allowing users to move easily in virtual environments is crucial for high-quality experiences in such collaborative VR applications. This paper focuses on redirected walking technology (RDW) to allow users to move beyond the confines of the limited physical environments (PE). The existing RDW methods lack the scheme to coordinate multiple users in different PEs, and thus have the issue of triggering too many resets for all the users. We propose a novel multi-user RDW method that is able to significantly reduce the overall reset number and give users a better immersive experience by providing a more continuous exploration. Our key idea is to first find out the "bottleneck" user that may cause all users to be reset and estimate the time to reset, and then redirect all the users to favorable poses during that maximized bottleneck time to ensure the subsequent resets can be postponed as much as possible. More particularly, we develop methods to estimate the time of possibly encountering obstacles and the reachable area for a specific pose to enable the prediction of the next reset caused by any user. Our experiments and user study found that our method outperforms existing RDW methods in online VR applications.