Vehicle detection and tracking in video

We present a scheme for vehicle detection and tracking in video. The proposed method effectively combines statistical knowledge about the class of vehicles with motion information. The unknown distribution of the image patterns of vehicles is approximately modeled using higher-order statistical information derived from sample images. Statistical information about the background is learnt "on the fly". A motion detector identifies regions of activity. The classifier uses a higher-order statistical closeness measure to determine which of the objects actually correspond to moving vehicles. The tracking module uses position co-ordinates and difference measurement values for correspondence. Results on real video sequences are given.