文献类型：期刊文献

英文题名：Driver fatigue detection based on eye state

作者：Lin, Lizong[1];Huang, Chao[1];Ni, Xiaopeng[1];Wang, Jiawen[1];Zhang, Hao[1];Li, Xiao[1];Qian, Zhiqin[1]

机构：[1]E China Univ Sci & Technol, Sch Mech & Power Engn, Robot Lab, Shanghai 200237, Peoples R China

年份：2015

卷号：23

起止页码：S453

外文期刊名：TECHNOLOGY AND HEALTH CARE

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000356537900032)】；

语种：英文

外文关键词：Driver fatigue detecting; eyes detecting and locating; PERCLOS

摘要：BACKGROUND: Nowadays, more and more traffic accidents occur because of driver fatigue. OBJECTIVE: In order to reduce and prevent it, in this study, a calculation method using PERCLOS (percentage of eye closure time) parameter characteristics based on machine vision was developed. It determined whether a driver's eyes were in a fatigue state according to the PERCLOS value. METHODS: The overall workflow solutions included face detection and tracking, detection and location of the human eye, human eye tracking, eye state recognition, and driver fatigue testing. The key aspects of the detection system incorporated the detection and location of human eyes and driver fatigue testing. The simplified method of measuring the PERCLOS value of the driver was to calculate the ratio of the eyes being open and closed with the total number of frames for a given period. RESULTS: If the eyes were closed more than the set threshold in the total number of frames, the system would alert the driver. CONCLUSION: Through many experiments, it was shown that besides the simple detection algorithm, the rapid computing speed, and the high detection and recognition accuracies of the system, the system was demonstrated to be in accord with the real-time requirements of a driver fatigue detection system.