Paper Info
Title
Virtual Reality Sickness Predictor: Analysis of visual-vestibular conflict and VR contents
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 %.
Year
DOI
Venue
2018
10.1109/QoMEX.2018.8463413
2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX)
Keywords
Field
DocType
Virtual Reality,VR sickness,Quality of Experience,Subjective Sickness Assessment
Computer vision,Virtual reality,Computer science,Visualization,Human visual system model,Motion perception,Feature extraction,Optical head-mounted display,Artificial intelligence,Perception,Virtual reality sickness
Conference
ISBN
Citations 
PageRank 
978-1-5386-2606-1
2
0.42
References 
Authors
18
5
Name
Order
Citations
PageRank
Jinwoo Kim11918168.52
Woojae Kim222.78
Sewoong Ahn3204.49
kim j kim jinwoo4135.38
Sanghoon Lee574097.47