Using the Active Appearance Model to detect driver fatigue

Driver fatigue is a major cause of accidents on roads. We present a video-based driver fatigue detection system, which uses the Active Appearance Model as a means to track rigid and non-rigid motion of a face in an input video sequence. We propose an Active Appearance Model specific to the ocular region of the face to place greater focus on the eyes, as fatigue cues based on ocular features, such as blink rate, are considered robust indicators of fatigue. This specific model is used to estimate eye-blinks, and further, secondary cues such as head-nodding. Results show that the proposed model can effectively detect eye-blinks. Finally, we evaluate tracking performance and blink estimation on two test subjects.