The paper proposes an advanced driver-assistance system that correlates the driver’s head pose to road hazards by analyzing both simultaneously. In particular, we aim at the prevention of rear-end crashes due to driver fatigue or distraction. We contribute by three novel ideas: Asymmetric appearance-modeling, 2D to 3D pose estimation enhanced by the introduced Fermat-point transform, and adaptation of Global Haar (GHaar) classifiers for vehicle detection under challenging lighting conditions. The system defines the driver’s direction of attention (in 6 degrees of freedom), yawning and head-nodding detection, as well as vehicle detection, and distance estimation. Having both road and driver’s behaviour information, and implementing a fuzzy fusion system, we develop an integrated framework to cover all of the above subjects. We provide real-time erformance analysis for real-world driving scenarios.
کلید واژگان :Driver Distraction Detection, ADAS, Active Appearance Modelling, Shape Modelling, Head Pose Estimation, Fuzzy Fusion, Advanced Driver Assistance Systems
ارزش ریالی : 300000 ریال
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