论文标题
部分可观测时空混沌系统的无模型预测
ENI: Quantifying Environment Compatibility for Natural Walking in Virtual Reality
论文作者
论文摘要
我们提出了一个新颖的指标，以分析虚拟现实中自然行走的物理环境与虚拟环境之间的相似性。我们的方法是一般的，可以应用于任何一对物理和虚拟环境。我们使用基于符合约束的Delaunay三角形和可见性多边形的几何技术来计算环境导航不兼容性（ENI）度量，可用于衡量执行同时导航的复杂性。我们演示了ENI在一对环境中突出显示不兼容的区域的应用，指导虚拟环境的设计，以使其与固定的物理环境更加兼容，并评估不同重定向步行控制器的性能。我们使用模拟和两项用户研究来验证ENI度量。我们的模拟和用户研究的结果表明，在环境对中，我们的公制将其确定为更可导航，用户可以步行更长的时间，然后才与物理环境中的对象碰撞。总体而言，ENI是第一个可以自动识别物理和虚拟环境中高兼容性区域的通用指标。我们的项目网站可在https://gamma.umd.edu/eni/上获得。
We present a novel metric to analyze the similarity between the physical environment and the virtual environment for natural walking in virtual reality. Our approach is general and can be applied to any pair of physical and virtual environments. We use geometric techniques based on conforming constrained Delaunay triangulations and visibility polygons to compute the Environment Navigation Incompatibility (ENI) metric that can be used to measure the complexity of performing simultaneous navigation. We demonstrate applications of ENI for highlighting regions of incompatibility for a pair of environments, guiding the design of the virtual environments to make them more compatible with a fixed physical environment, and evaluating the performance of different redirected walking controllers. We validate the ENI metric using simulations and two user studies. Results of our simulations and user studies show that in the environment pair that our metric identified as more navigable, users were able to walk for longer before colliding with objects in the physical environment. Overall, ENI is the first general metric that can automatically identify regions of high and low compatibility in physical and virtual environments. Our project website is available at https://gamma.umd.edu/eni/.
