Natural Light, Computer Vision-based Driver Fatigue Detection

With the high development of the highway and the quick increase of the number of people having car, the number of traffic accidents are increasing obviously. Driver fatigue problem is one of the important factors that cause traffic accidents. In New York about 10 percent of accidents are fatigue-related in 68 thousand accidents that caused without environment factors and about one fourth of the drivers have ever driven with fatigue. In china, driver fatigue is also the main cause of accidents. It is studied that the behavior of a driver without sleep in 17 to 19 hours equals to a drunk driver whose alcohol concentration is 0.05 percent Therefore, how to supervise and avoid fatigue driving efficiently is one of the significant problems.Since 1990s, with the development of the computer and integrate circuit, the research of driver fatigue has further developed and a lot of valuable products appeared. Such as The Drowsy Driver Detection System and The Psychomotor Vigilance Test in America, The clear-headed strip in Japan. However, those products are not practicable, other more valuable methods are undergoing rigorous evaluation and design.In mis thesis, we investigate and contrast the principles of current methods and technologies for driver fatigue detection, and analyze the key problems and difficulties of these techniques, men propose a quick and effective driver fatigue method based on computer vision in natural illumination. We lay a camera on the panel to shoot the driver's face. Eye features, such as up-eyelid curvature and the distance of eyelid, which are cues for determining driver's state, are extracted from the video of face. Then using fuzzy data fusion we can determine even forecast the driver's state effectively.The contents of this paper are as following:1) Study the skin distribution, the relation of illumination and color space and then segment skin in the color pace which the illumination influences little.2) Study and analyze many eye location and eye tracking methods and propose...