Computationally Efficient Vehicle Tracking for Detecting Accidents in Tunnels
It is becoming increasingly important to construct tunnel for transportation time and space utilization. To avoid the large scale of damages of vehicle accident in the tunnel, it is necessary to have a tunnel accidents monitoring system to minimize and discover the accidents as fast as possible. In this paper, a moving and stopped vehicle detection algorithm is proposed. It Detecting vehicle based on morphological size information of object according to distance and Adaboost algorithm. Kalman filter and LUV color informations of rear lamp are used to detect stopped vehicles. Results of computer simulations show that proposed algorithm increases detection rate more than other detection algorithms.
KeywordsBackground estimation Adaboost Algorithm Kalman Filter LUV color
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