Computer vision based gaze tracking for accident prevention

Distracted driving is one of the main causes of vehicle collisions in India. Passively monitoring a driver's activities constitutes the basis of an automobile safety system that can potentially reduce the number of accidents by estimating the driver's focus of attention. Automotive vehicles are increasingly being equipped with accident avoidance and warning systems for avoiding the potential collision with an external object, such as another vehicle or a pedestrian. Upon detecting a potential factor, such systems typically initiate an action to avoid the collision and/or provide a warning to the vehicle operator. In this paper a complete accident avoidance system is proposed by determining the driver's behavior. As the main causes of vehicle accident were related to human factors, they could be labeled in one of the two main driver's distraction categories (Alcohol Consumption, Drowsiness and distracted vision). The aim of the proposed system is to help in analyzing the factors associated with driver's behavior for the development of accident avoidance systems. The main causes of the traffic accidents, discovered in the analysis of the driver behavior with the help of our system, will be used for the development of assistant devices and alarm systems that could help the driver to avoid risky situations. In this project we are implementing two image processing tool to get the facial geometry based eye region detection for eye closure identification, combined tracking and detection of vehicles. Frequencies of eye blinking and eye closure are used as the indication of sleepy and warning sign is then generated for recommendation; (b) outside an ego vehicle, road traffic is also analyzed.