An improved likelihood model for eye tracking
Computer Vision and Image Understanding
Computer Vision and Image Understanding
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We present an automotive-grade, real-time, vision-based Driver State Monitor. Upon detecting and tracking the driverýs facial features, the system analyzes eye-closures and head pose to infer his/her fatigue or distraction. This information is used to warn the driver and to modulate the actions of other safety systems. The purpose of this monitor is to increase road safety by preventing drivers from falling asleep or from being overly distracted, and to improve the effectiveness of other safety systems.