The driver fatigue detection is one of the most prospective commercial applications of facial expression recognition technology. Current facial features tracking techniques faces three challenges: 1) variety of light conditions and head orientation failure of some or all the facial features, 2) multiple and non rigid object tracking, and 3) facial feature occlusion. In this paper, we propose a new approach. First, the single camera (webcam) is used to detect face under various lighting conditions. The detected face is used to track facial features by using color model. Because color processing is very fast that mean time requirement is less. And from tracked facial features we predict the head motions in up-down and left-right direction. Furthermore, face movement are assumed to be smooth so that a facial features can be tracked with three point algorithm. Simultaneous use of YCbCr color mode, three point algorithms and the Geometric model greatly increases the prediction accuracy for each feature position. The experimental results shows validity of our approach to a real life facial tracking under various light condition, head orientations and facial expression.

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Face detection Facial feature tracking color model geometric model