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DreamWalk: Dynamic Remapping and Multiperspectivity for Large-Scale Redirected Walking
  • +1
  • Yuan Xiong,
  • Tong Chen,
  • Tianjing Li,
  • Zhong Zhou
Yuan Xiong
State Key Laboratory of Virtual Reality Technology and Systems
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Tong Chen
State Key Laboratory of Virtual Reality Technology and Systems
Author Profile
Tianjing Li
State Key Laboratory of Virtual Reality Technology and Systems
Author Profile
Zhong Zhou
State Key Laboratory of Virtual Reality Technology and Systems

Corresponding Author:[email protected]

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Abstract

Redirected walking (RDW) provides an immersive user experience in virtual reality applications. In RDW, the size of the physical play area is limited, which makes it challenging to design the virtual path in a larger virtual space. Mainstream RDW approaches rigidly manipulate gains to guide the user to follow predetermined rules. However, these methods may cause simulator sickness, boundary collision, and reset. Static mapping approaches warp the virtual path through expensive vertex replacement in the stage of model pre-processing. They are restricted to narrow spaces with non-looping pathways, partition walls, and planar surfaces. These methods fail to provide a smooth walking experience for large-scale open scenes. To tackle these problems, we propose a novel approach that dynamically redirects the user to walk in a non-linear virtual space. More specifically, we propose a Bezier-curve-based mapping algorithm to warp the virtual space dynamically and apply multiperspective fusion for visualization augmentation. We conduct comparable experiments to show its superiority over state-of-the-art large-scale redirected walking approaches on our self-collected photogrammetry dataset.
29 May 2023Submitted to Computer Animation and Virtual Worlds
29 May 2023Submission Checks Completed
29 May 2023Assigned to Editor
18 Jun 2023Reviewer(s) Assigned
26 Jun 2023Review(s) Completed, Editorial Evaluation Pending
26 Jun 2023Editorial Decision: Accept