A method for multi-person mobile virtual reality fire evacuation drills based on pose estimation: Consistency of vision and perception

虚拟现实 增强现实 一致性(知识库) 计算机科学 更安全的 姿势 人机交互 感知 过程(计算) 混合现实 移动设备 模拟 人工智能 计算机安全 心理学 神经科学 操作系统
作者
Pei Dang,Jun Zhu,Yungang Cao,Jianlin Wu,Weilian Li,Ya Hu,Jigang You,Lin Fu
出处
期刊:Safety Science [Elsevier BV]
卷期号:170: 106334-106334 被引量:8
标识
DOI:10.1016/j.ssci.2023.106334
摘要

Fire disasters present significant risks, emphasizing the need for effective evacuation drills. Traditional drills in real environments have limitations such as safety risks and poor repeatability. Immersive Virtual Reality (iVR) provides a safer, more engaging alternative, but early iVR-based drills were restricted due to hardware limitations. The advent of mobile virtual reality has overcome some of these restrictions. However, challenges remain in multi-person evacuation scenarios, such as difficulties in relative positioning and the real time interaction of evacuees. This study addresses these issues using pose estimation for accurate positioning in virtual reality devices. Furthermore, we developed a framework for conducting evacuation drills in a real environment using mobile virtual reality, ensuring consistency in participants' visual and perceptual experiences. Subsequently, we designed two experiments to validate this methodology and framework. The experimental results demonstrated that the evacuation process, using pose estimation, effectively eliminates cumulative error, maintaining an approximate error of 0.04 m between the real and virtual environments. Participants also reported having a better experience and found it easier to interact with others during the mobile virtual reality evacuation.
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