This paper presents a non-intrusive fatigue detection system based on the video analysis of drivers. The focus of the paper is on how to detect yawning which is an important cue for determining driver's fatigue. Initially, the face is located through Viola-Jones face detection method in a video frame. Then, a mouth window is extracted from the face region, in which lips are searched through spatial fuzzy c-means (s-FCM) clustering. The degree of mouth openness is extracted on the basis of mouth features, to determine driver's yawning state. If the yawning state of the driver persists for several consecutive frames, the system concludes that the driver is non-vigilant due to fatigue and is thus warned through an alarm. The system reinitializes when occlusion or misdetection occurs. Experiments were carried out using real data, recorded in day and night lighting conditions, and with users belonging to different race and gender. The paper is arranged as follows: In Section 2, a review of previous studies in this line is presented. Section 3 describes the overall system architecture, explaining its main parts. The experimental results are shown in Section 4 and finally the authors present the conclusion and future studies in Section 5.
Automatic fatigue detection of drivers through yawning analysis
2009
8 Seiten, 5 Bilder, 9 Quellen
Conference paper
English
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