Localization and Prediction of Visual Targets' Position in Immersive Virtual Reality

Author:

Dozio Nicolò1,Rozza Ludovico2,Lukasiewicz Marek S.1,Colombo Alessandro2,Ferrise Francesco1

Affiliation:

1. Politecnico di Milano Department of Mechanical Engineering Milan, 20156, Italy

2. Politecnico di Milano Department of Electronics, Information, and Bioengineering Milan, 20123, Italy

Abstract

Abstract Modern driver-assist and monitoring systems are severely limited by the lack of a precise understanding of how humans localize and predict the position of neighboring road users. Virtual Reality (VR) is a cost-efficient means to investigate these matters. However, human perception works differently in reality and in immersive virtual environments, with visible differences even between different VR environments. Therefore, when exploring human perception, the relevant perceptive parameters should first be characterized in the specific VR environment. In this paper, we report the results of two experiments that were designed to assess localization and prediction accuracy of static and moving visual targets in a VR setup developed using broadly available hardware and software solutions. Results of the first experiment provide a reference measure of the significant effect that distance and eccentricity have on localization error for static visual targets, while the second experiment shows the effect of time variables and contextual information on the localization accuracy of moving targets. These results provide a solid basis to test in VR the effects of different ergonomics and driver-vehicle interaction designs on perception accuracy.

Publisher

MIT Press

Subject

Computer Vision and Pattern Recognition,Human-Computer Interaction,Control and Systems Engineering,Software

Reference43 articles.

1. Evidence for attentional processing in spatial localization;Adam;Psychological Research,2008

2. Are experienced drivers more likely than novice drivers to benefit from driving simulations with a wide field of view?;Alberti;Transportation Research Part F: Traffic Psychology and Behaviour,2014

3. Age and visual search: Expanding the useful field of view;Ball;Journal of the Optical Society of America A,1988

4. Visual attention problems as a predictor of vehicle crashes in older drivers.;Ball;Investigative Ophthalmology and Visual Science,1993

5. Three decades of driver assistance systems: Review and future perspectives;Bengler;IEEE Intelligent Transportation Systems Magazine,2014

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3