Behavior Metric for Evaluating the Impact of Visual Distortions on User Viewport in a VR Navigation Experience
Résumé
Visual distortions significantly impact user experience in virtual reality (VR). Understanding these effects is essential for delivering a higher-quality VR experience. However, existing studies focus on distortions from image capturing, processing, or display, relying largely on self-reported scores. The impact of visual distortions on viewport caused by simulated visual impairments in VR remains underexplored, despite its importance in creating realistic VR experiences, raising public awareness, and studying the effects of visual impairment. This study proposes a Hidden Markov Model (HMM)-based behavior entropy metric to measure the effects of visual distortions on a user's viewport in a 6-Degrees-of-Freedom (DoF) VR navigation experience. An Orientation and Mobility (O&M) VR scenario designed to assess the navigation performance of visually impaired individuals was used for the experiment. Results reveal a relationship between behavior entropy and distortion severity: slight to moderate distortions reduce entropy, while severe distortions cause a significant decline. Additionally, behavior entropy correlates with O&M test performance metrics, indicating its potential as an objective behavioral measure of VR navigation performance. These findings highlight the value of behavior analysis in evaluating VR user experience, offering a new analytical perspective on visual distortion effects and expanding applications of behavior analysis in multidisciplinary research.
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