A Practical Eye State Recognition Based Driver fatigue detection method

被引：0
作者：
Wang, Huan [1 ,2 ]
Chen, Yong [1 ,2 ]
Wang, Qiong [1 ,2 ]
Ren, Mingwu [1 ,2 ]
Zhao, Chunxia [1 ,2 ]
Yang, Jingyu [1 ,2 ]
机构：
[1] Nanjing Univ Sci & Technol, Sch Comp Sci, Nanjing 210094, Peoples R China
[2] Nanjing Inst Technol, Sch Commun Engn, Nanjing 211167, Peoples R China
来源：
PROCEEDINGS OF THE 2009 CHINESE CONFERENCE ON PATTERN RECOGNITION AND THE FIRST CJK JOINT WORKSHOP ON PATTERN RECOGNITION, VOLS 1 AND 2 | 2009年
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D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Driving fatigue detection is a key technique in vehicle active safety. In this paper, a practical driver fatigue detection algorithm is proposed) it employs sequential detection and temporal tracking to detect human face, which combines the superiorities of both Adaboost and Mean-Shift algorithm; A morphologic filter method is given to localize the pair of eyes in the detected face area. Then multiple image features are exploited to recognize open state or close state. Various tests demonstrated that it has a performance of high detection precision and fast processing speed. To this end, it can be effectively and efficiently used in vehicle active safety systems.
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页码：423 / +
页数：2
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