Abstract
Recently, extensive research on driver assistance systems has focused on applications such as lane departure warnings, traffic sign recognition, and pedestrian and vehicle detection systems. This paper presents a real-time vehicle detection and tracking system for detecting on-road vehicles in front of a vehicle with mobile camera. The system consists of two main steps: generating candidates with respect to a vehicle by using the AdaBoost learning algorithm, and verifying the candidates according to symmetry measurement and horizontal and vertical edge analysis. The proposed system was experimentally proven to be effective in various traffic scenarios.
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