A detection model for driver's unsafe states based on real-time face-vision

The auto industry has developed fast in the last 100 years. Although it brings us convenience, more and more traffic accidents are happening every day. There are many factors which can cause a car accident. Based on the record of a large number of accidents, fatigue is one of the most important factors. Additionally, driver's distraction and conversations with passengers during driving can lead to serious results. In this paper, a real-time vision-based model is proposed for monitoring driver's unsafe states, including fatigue state, distraction state and talking state, etc. By analyzing driver's real-time face vision, a method for detecting driver's fatigue, distraction and talking states is given. Also, the model is its extreme high speed and very simple equipment. It can run at about 20 frames per second in video with 640*480 resolutions on a normal computer platform.