Driver fatigue detection and early warning

In recent years, with the rapid increase in the number of cars in various countries, traffic accidents have also occurred frequently. Among them, traffic accidents caused by driver fatigue driving account for a large proportion, and how to improve the safety of driver driving has become a key issue. Therefore, this article proposes a driver face recognition and fatigue driving warning method based on computer vision. This article first uses the Adaboost face detection algorithm for face detection, and uses the Dlib toolkit to label facial key points. Then, by using these key points, the eye aspect ratio, mouth aspect ratio, and Euclidean distance between the two feature points of the nose are calculated. These three parameters are used as fatigue feature values for fatigue state judgment and corresponding warning experiments are given. Tests have shown that this method can reflect the fatigue status of drivers in real time and has good detection performance.