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\begin{document}

\title{DreamWalk: Dynamic Remapping and Multiperspectivity for Large-Scale
Redirected Walking}



\author[1]{Yuan Xiong}%
\author[1]{Tong Chen}%
\author[1]{Tianjing Li}%
\author[1]{Zhong Zhou}%
\affil[1]{State Key Laboratory of Virtual Reality Technology and Systems}%


\vspace{-1em}



  
  \date{May 18, 2024}


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\begin{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.%
\end{abstract}%



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