A PERCLOS-Based Driver Fatigue Recognition Application for Smart Vehicle Space

The paper selected PERCLOS to evaluate driving fatigue after the comparison of various fatigue detection methods for smart vehicle space. We detected driver fatigue status by measuring the proportion of eyes closed in a certain period of time and the continued closure time. On the basis of the Haar-Like feature, AdaBoost algorithm was adopted to produce the strong classifier for face and eye detection. AdaBoost detector is employed firstly to determine human face region, locate the eyes in this region, and using an improved template matching method to detect eye States. Experiments show that this method can identify eye state rapidly and real-timely under natural light conditions, the algorithm has better robustness and real-time.