| In modern society, with the economic conditions getting better, more and more vehicles are produced. So many vehicles bring about the rapid development of traffic transportation and the traffic accidents happen frequently. Fatigue driving is one of the most important reasons which cause traffic accidents. When the driver is fatigue driving, he is often distractive, unresponsive, consciousness, and to more important, he is too tired to know himself in a danger state of fatigue driving. If we can give warning timely, remind the driver to rest, it is possible to avoid a traffic accident. Therefore, how to find a real-time and accurate fatigue driving detection technology and give warning is an important issue to be explored by researchers. It has scientific and realistic significance for maintaining the traffic safety, people’s lives and property.This paper first introduces various fatigue driving detection methods, establishes the research direction based on computer vision method to detect directly, which has a low cost, contactless etc. advantages. Next, we focus on face detection, eye location and contour extraction, fatigue determining. The detection system is logically divided into two parts:the standard model training module and real-time fatigue detection module. The standard model training module can be divided into:video camera image acquisition module, frame image face detection module, eye contour feature extraction and model storage module; Real-time fatigue detection module can be divided into: video camera image acquisition module, frame image face detection module, eye contour feature extraction and matching module, PERCLOS fatigue determining module.The development environment is:VS2005. With Intel’s OpenCV library, we studied and proofed the driver fatigue detection algorithm. A set of software system was developed. The whole system basically realized fatigue driver detection. It has a processing speed of5-7frames which meets the requirement of real-time process. |
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