Hypovigilance Detection Based on Eyelids Behavior Study
The supervision of people in special circumstances, having as their purpose detecting risk situations, is an area which has many applications. In this context we are interested, in this paper, the problems of driver drowsiness detection based on video analysis. We describe a new approach to detect reduced alertness automatically, to prevent the driver. Unlike many other works, our noninvasively approach is based only on the analysis of geometric features captured form faces video sequence without any electronics elements related to human.
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