Current Status and Development Trends of Animation and Virtual Cinematography Techniques in VR Motion Sickness Prevention Design
Year: 2025
Type: article
Abstract: Virtual Reality (VR) technology has rapidly been adopted across entertainment, education, healthcare, and industrial sectors; however, cybersickness remains a significant barrier to user engagement and comfort. This paper reviews the mechanisms underlying VR-induced dizziness, emphasizing sensory conflict, postural instability, and latency as primary contributing factors. It further examines both subjective and objective evaluation methods, including questionnaires, physiological indicators, eye-tracking, and postural sway measurements. Building on this foundation, the study systematically analyzes key technical parameters such as frame rate, Field of View (FOV), and camera motion and their influence on reducing visual–vestibular conflict. Additionally, it explores animation and virtual cinematography techniques, including camera path design, easing functions, and frame-by-frame stabilization, as essential strategies for mitigating discomfort while enhancing immersion. Existing studies demonstrate that single-parameter optimizations provide limited relief due to threshold effects and individual differences, whereas integrated multi-parameter approaches show greater potential for effectiveness. The article proposes a unified framework that combines technical and aesthetic strategies, with an emphasis on Artificial Intelligence (AI)-driven adaptation and cross-modal augmentation. This synthesis not only bridges gaps in fragmented research but also offers practical guidance for future VR content creation and hardware development. By advancing systematic design strategies, the paper contributes to establishing a more rigorous foundation for improving user comfort, immersive quality, and the long-term scalability of VR systems.
Author: Yanxiang Wang
Institution: Beijing Normal-Hong Kong Baptist University
Language: English
Subfield: Human-Computer Interaction
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4415156209
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