Mitigation of VR Sickness during Locomotion with a Motion-Based Dynamic Vision Modulator

Guanghan Zhao, Jason Orlosky, Steven Feiner, Photchara Ratsamee, Yuki Uranishi

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


In virtual reality, VR sickness resulting from continuous locomotion via controllers or joysticks is still a significant problem. In this paper, we present a set of algorithms to mitigate VR sickness that dynamically modulate the user’s field of view by modifying the contrast of the periphery based on movement, color, and depth. In contrast with previous work, this vision modulator is a shader that is triggered by specific motions known to cause VR sickness, such as acceleration, strafing, and linear velocity. Moreover, the algorithm is governed by delta velocity, delta angle, and average color of the view. We ran two experiments with different washout periods to investigate the effectiveness of dynamic modulation on the symptoms of VR sickness, in which we compared this approach against baseline and pitch-black field-of-view restrictors. Our first experiment made use of a just-noticeable-sickness design, which can be useful for building experiments with a short washout period.

Original languageEnglish (US)
Pages (from-to)1-13
Number of pages13
JournalIEEE Transactions on Visualization and Computer Graphics
StateAccepted/In press - 2022
Externally publishedYes


  • Angular velocity
  • contrast manipulation
  • Image color analysis
  • Legged locomotion
  • Modulation
  • Optical flow
  • shading and rendering
  • Teleportation
  • vision modulation
  • Visualization
  • VR sickness

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design


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