REAL TIME DRIVER DROWSINESS DETECTION USING CONVOLUTIONAL NEURAL NETWORK

Now a days the drowsiness of driver is leading cause for major accidents. The regular monitoring of drivers drowsiness is one among the simplest solution to scale back the accidents caused by drowsiness. It is vital to style a road accidents prevention system by detecting driver’s drowsiness, determining the extent of driver inattentiveness and provides a warning when an impending danger exists. This paper explains a driver drowsy detection system using video processing, analysing duration and head posture estimation to verify the driving force vigilance state. We capture colour, infrared, depth and 3D body pose information from six views and densely label the videos with a hierarchical annotation scheme, leading to 83 categories.