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Navigation in multiscale virtual environments in virtual reality

Resource type
Thesis type
(Thesis) Ph.D.
Date created
Author: Lee, Jong-in
Navigation in virtual environments, particularly multiscale virtual environments (MVEs), presents fundamental challenges. MVEs, spanning from atomic to galactic scales, require users to control various navigation parameters, including scale and travel speed, for efficient exploration. In such environments, users must constantly adjust their speed to traverse varying distances while maintaining accuracy in reaching target points of interest (POIs) in distance. However, this necessitates complex navigation interfaces for parameter control, compounding the challenge, especially for novice users. Moreover, MVE navigation involves not only movement in three dimensions but also changes in scale, further complicating the user experience. Depth perception limitations in virtual reality (VR) exacerbate these challenges, leading to frequent spatial disorientation. Additionally, maintaining spatial orientation while transitioning between different Levels-of-Scale (LoS) poses difficulties due to abrupt changes in spatial context, particularly evident during teleportation. To mitigate these challenges, this thesis introduces three novel navigation techniques tailored for MVEs in VR: automatic distance control for target-based locomotion, viewpoint transition techniques, and scaling techniques. The automatic distance control technique, presented at ACM VRST '20, addresses the challenge of maintaining accuracy in navigating varying distances within MVEs. Subsequently, viewpoint transition techniques, introduced at IEEE VR '23, aim to enhance spatial orientation during teleportation across different LoS. Finally, scaling techniques, yet to be published, offer solutions for managing scale changes seamlessly during navigation in MVEs. By addressing these challenges, the proposed techniques aim to improve the user experience in navigating MVEs, ultimately enhancing navigation performance and usability in VR.
119 pages.
Copyright statement
Copyright is held by the author(s).
This thesis may be printed or downloaded for non-commercial research and scholarly purposes.
Supervisor or Senior Supervisor
Thesis advisor: Stuerzlinger, Wolfgang
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