Yawning detection for monitoring driver fatigue based on two cameras

Abstract

Driver fatigue is one of the main reasons causing traffic accidents. Yawning is an important character of driver fatigue. Mouth geometric character represents state of driver. So driver's mouth detection and information extraction is especially important. This paper proposes to locate and track driver's mouth using two CCD cameras to detect driver's fatigue in real-time. One of them is with cloud platform control. Camera A, which is fixed, is mainly used to supply driver's head position. Camera B, which is controllable, is to locate driver's mouth and extract mouth information. First, collecting monitoring video of camera A (low resolution ratio) and locate driver's face using fast image processing algorithm. Second, we send commands to camera B (high resolution ratio) through serial port to make it shoot driver's head all the time according to face position in Camera A. Then we use haar-like features to detect driver's mouth in camera B and track it according to historical position. At last, yawning is detected by the ratio of mouth height and width. Through this method the resolution ratio of driver's mouth is higher than one camera and the feature information is more accuracy. It provides a better basis for driver fatigue judging.