Co-training algorithm based on on-line boosting for vehicle tracking

The current vehicle tracking algorithms cannot meet the requirements of high robustness in engineering application. A co-training algorithm based on on-line boosting for vehicle tracking is proposed. In this algorithm, first the vehicle region of interest is detected by vehicle-shadow feature and vehicle horizontal edge feature. Then the vehicle region of interest is verified by off-line classifiers which are learned from Haar feature and Adaboost algorithm. Finally, a co-training algorithm based on on-line boosting is used for further vehicle tracking, then the tracking window was reshaped according to the shadow of target vehicle. Experiments show that the proposed algorithm has high robustness and flexibility with good application prospects.