Edge-Centric Space Rescaling with Redirected Walking for Dissimilar Physical-Virtual Space Registration
PubDate: Aug 2023
Teams: KAIST
Writers: Dooyoung Kim, Woontack Woo
Abstract
We propose a novel space-rescaling technique for registering dissimilar physical-virtual spaces by utilizing the effects of adjusting physical space with redirected walking. Achieving a seamless immersive Virtual Reality (VR) experience requires overcoming the spatial heterogeneities between the physical and virtual spaces and accurately aligning the VR environment with the user’s tracked physical space. However, existing space-matching algorithms that rely on one-to-one scale mapping are inadequate when dealing with highly dissimilar physical and virtual spaces, and redirected walking controllers could not utilize basic geometric information from physical space in the virtual space due to coordinate distortion. To address these issues, we apply relative translation gains to partitioned space grids based on the main interactable object’s edge, which enables space-adaptive modification effects of physical space without coordinate distortion. Our evaluation results demonstrate the effectiveness of our algorithm in aligning the main object’s edge, surface, and wall, as well as securing the largest registered area compared to alternative methods under all conditions. These findings can be used to create an immersive play area for VR content where users can receive passive feedback from the plane and edge in their physical environment.
