A Practical Eye State Recognition Based Driver Fatigue Detection Method

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.