Abstract:

Since it is difficult to accurately locate and track facial key features in fatigue driving, we propose a new fatigue driving detection method based on the active shape model (ASM) and the skin color model. Firstly, we use the skin color model to detect the initial localization of the face region for the ASM. Secondly, eyes and mouths are tracked based on the ASM access to eye and mouth area. Thirdly, Canny operator is adopted for accurately locating of the two regions and the fatigue detection parameters are obtained. Finally, the fatigue detection is realized according to the percentage of eyelid closure over the pupil over time (PERCLOS) method. Given that the face detection based on the HSV color model is not influenced by posture and angle but is easy to be interfered by background, while the ASM has a good advantage of face key point tracking effect but has difficulty in the initial location, we combine the two methods which can achieve accurate eyes and mouth location and tracking. Experimental results show that the accuracy of eye detection can reach 90.7%, the accuracy of yawn detection can reach 83.3%, and the accuracy of fatigue detection is 91.4%.