A real-time system for monitoring driver fatigue
TRANSPORTATION PLANNING AND TECHNOLOGY(2016)
摘要
This paper presents a nonintrusive prototype computer vision system for real-time fatigue driving detection. First, we use Haar-like features to detect a driver's face and conduct tracking by introducing an improved Camshift algorithm. Second, we propose a new eye-detection algorithm that combines the Adaboost algorithm with template matching to reduce computational costs and add an eye-validation process to increase the accuracy of the detection rate. Third, and different from other methods focusing on detecting eyes using the bright pupil' effect, which only works well only for certain constrained lighting conditions, our method detects and estimates the iris center in the hue (H) channel of the hue, saturation, value color space and fits the iris with an ellipse. After extracting the eye fatigue features, we calculate the PERCLOS measurement for fatigue evaluation. This system has been tested on the IMM Face Database, which contains more than 200 faces, and in a real-time test. The experimental results show that the system possesses good accuracy and robustness.
更多查看译文
关键词
Driving fatigue,eye detection,template matching,ellipse fitting,fatigue evaluation
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要