Virtual Reality Sickness Predictor: Analysis of visual-vestibular conflict and VR contents

Jaekvung Kim, Woojae Kim, Sewoong Ahn, Jinwoo Kim, Sanghoon Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

Predicting the degree of sickness is an imperative goal to guarantee viewing safety when watching virtual reality (VR) contents. Ideally, such predictive models should be explained in terms of the human visual system (HVS). When viewing VR contents using a head mounted display (HMD), there is a conflict between user's actual motion and visually perceived motion. This results in an unnatural visual-vestibular sensory mismatch that causes side effects such as onset of nausea, oculomotor, disorientation, asthenopia (eyestrain). In this paper, we propose a framework called VR sickness predictor (VRSP) using the interaction model between user's motion and the vestibular system. VRSP extracts two types of features: a) perceptual motion feature through a visual-vestibular interaction model, and b) statistical content feature that affects user motion perception. Furthermore, we build a VR sickness database including 36 virtual scenes to evaluate the performance of VRSP. Through rigorous experiments, we demonstrate that the correlation between the proposed model and the subjective sickness score yields 72 %.

Original languageEnglish
Title of host publication2018 10th International Conference on Quality of Multimedia Experience, QoMEX 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781538626054
DOIs
Publication statusPublished - 2018 Sep 11
Event10th International Conference on Quality of Multimedia Experience, QoMEX 2018 - Sardinia, Italy
Duration: 2018 May 292018 Jun 1

Publication series

Name2018 10th International Conference on Quality of Multimedia Experience, QoMEX 2018

Other

Other10th International Conference on Quality of Multimedia Experience, QoMEX 2018
CountryItaly
CitySardinia
Period18/5/2918/6/1

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All Science Journal Classification (ASJC) codes

  • Media Technology
  • Safety, Risk, Reliability and Quality

Cite this

Kim, J., Kim, W., Ahn, S., Kim, J., & Lee, S. (2018). Virtual Reality Sickness Predictor: Analysis of visual-vestibular conflict and VR contents. In 2018 10th International Conference on Quality of Multimedia Experience, QoMEX 2018 [8463413] (2018 10th International Conference on Quality of Multimedia Experience, QoMEX 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/QoMEX.2018.8463413