Fatigue Driving Detection Based on Multi Feature Fusion

In recent years, the number of car has been increasing, and car has gradually become an indispensable mean of transportation for people to travel. However, along with the rapid growth of car brings convenience to people's life, it also brings many negative effects to the development of road traffic. More and more traffic accidents have happened, and most traffic accidents are caused by fatigue driving. In order to reduce traffic accidents caused by fatigue driving, many methods have been proposed. However, these methods cannot guarantee the accuracy and speed of detection at the same time. So, a fatigue driving detection method based on multi feature fusion is presented in this paper. Firstly, MTCNN is used to improve the face tracking algorithm based on MedianFlow. Then a new face key points detection model based on CNN is proposed, the result of face key points detection can be used to locate the eyes. Finally, information such as eye closing time, blinking frequency and head position are fused to detect fatigue driving. Experimental results show that the fatigue driving detection method proposed in this paper has a good result on speed and accuracy.