Real Time Driver Fatigue Detection Based on SVM Algorithm

Among the causes of the traffic accidents driver drowsiness comes at one of the first places. According to the literature some work has been done in driver fatigue detection. This paper proposes a Real Time Driver Fatigue Detection Based on Support Vector Machine (SVM) Algorithm. Fatigue detection mainly focuses on drivers' face expressions and behaviors. OpenCV and Dlib libraries were utilized to detect the expressions of drivers' faces. The proposed system has five stages: PERCLOS, count of yawn, internal zone of the mouth opening, count of eye blinking and head detection to extract attributes from real time video. Subsequently, facial expressions were trained with SVM. In this study an SVM-based driver fatigue detection is recommended and the tests showed that the accuracy rate of fatigue detection is up to 97.93%.