基于运动感知和眼动特征的视觉诱导晕动症检测研究

Detection of VIMS Based on Motion Perception and Eye Movement Characteristics

目的视觉诱导晕动症是造成用户VR体验舒适度降低的主要原因。如何有效检测并减少视觉诱导晕动症给用户带来的影响是VR产品普及过程中一大亟待解决的问题。旨在探讨视觉诱导晕动症检测方法。方法采用虚拟现实漫游实验收集场景变化参数和用户眼动数据,并从用户运动感知和眼动特征两方面进行数据分析。结果场景变化会引发用户的运动感知,用户本身对于视觉刺激的晕动症易感性会使这种运动感知诱发不同程度的视觉诱导晕动症症状,这种差异体现在眼动特征中。采用运动感知和眼动特征指标构建视觉诱导晕动症检测模型。结论建立的视觉诱导晕动症检测模型可以为实时视觉诱导晕动症检测提供理论支撑。

Objective Visually Induced Motion Sickness(VIMS)is the main reason for the decrease comfort of VR experience.How to effectively detect and reduce the impact of VIMS is a major problem to be solved in the popularization of VR products.The research aims to explore how to detect VIMS.Methods Virtual reality roaming experiment was used to collect scene change parameters and user eye movement data,and the data were analyzed in terms of both user motion perception and eye movement characteristics.Results Scene changes can trigger motion perception,and users'susceptibility to VIMS caused by visual stimuli induced different degrees of VIMS.This difference was reflected in the eye movement characteristics.Therefore,motion perception and eye movement characteristics can be extracted to construct detection model of VIMS.Conclusion The established model for the detection of visually induced motion sickness can provide theoretical support for real-time visually induced motion sickness detection.