Design and Implementation of Multi feature Face Detection Anti fatigue Driving System

In order to better prevent the problem of driver fatigue driving and protect the safety of people’s lives and property, many automobile manufacturers and scientific research institutions have carried out research on this. Detection methods based on physiological characteristics, such as heart rate detection, detection methods based on vehicle driving information and detection methods based on driver behavior characteristics, came into being as a solution for fatigue driving detection. The first two methods cannot be put into large-scale use under actual production conditions due to their problems of limiting the driver’s body and detecting the low accuracy and accuracy rate, respectively. In response to the above problems,this paper adopts the detection method based on the driver’s behavior characteristics, combined with the depth learning algorithm which is widely used and has significant advantages in the field of computer vision, selects the method of multi feature comprehensive judgment as the innovation point, proposes to use the head posture characteristics as the basis for comprehensive judgment, to judge whether there is the behavior of nodding due to drowsiness, In this way, an efficient and reliable fatigue driving detection scheme is designed and implemented, and focuses on the research of the algorithm based on the state change of the eyes, Using Python and OpenCV function library to simulate related algorithms, the feasibility of the software implementation process is verified. It realizes real-time and accurate monitoring and detection of whether the driver is in a state of fatigue driving. [1]