International Journal of Computer Science Issues

More than a traditional journal...

This paper presents a real time multiclass vehicle detection and tracking system. The system uses a combination of machine learning and feature analysis to detect and track the vehicles on the road. Multiclass SVM and PCA methods are utilized to create multiclass training samples. The online classifiers are trained using these samples to achieve detection and classification of vehicles in video sequences of traffic scenes. The detection results provide the system used for tracking. Each class vehicle is tracked by SIFT method. The system combines the advantages of both multiclass detection and tracking in a single framework. Experimental results from highway scenes are provided which demonstrate the effectiveness of the method.