Motion Multi-Vehicle Recognition and Tracking in Stable Scene

Abstract

A method for moving multi-target recognition and tracking in stable scene is presented. Optical flow is used to extract the velocity of pixels, and targets are recognized by combining motion character points obtained by binary discrete wavelet transforms (BDWT). A discrete kalman filter is used to track targets in the follow-up frames; the center and scale of tracking window are updated by a Mexico wavelet kernel function mean shift method which is embedded into the discrete kalman filter framework to stabilize the trajectories of the targets for robust tracking during mutual occlusion. The method is tested on several frame sequences and shown to achieve robust and reliable frame-rate recognition and tracking.