Abstract: A multi-resolution optical flow tracking algorithm based on wavelet pyramid is proposed, since the LK (Lucas-Kanade) algorithm for sparse optical flow cannot steadily and rapidly track the moving objects. By virtue of the idea of multi-resolution tracking and relevant computation, the algorithm decomposes the displacement of the object within the wavelet pyramid to enable the displacement to meet the requirement of the LK algorithm for tracking accurately the rapidly moving objects. Extracting the feature of moving vehicles, multi-scale Harris corner detection is proposed to adapt to the complicated traffic situation, thus solving the problem that the conventional Harris corner detection which may neglect corner points and their non-uniform distribution. Experimental results show that in this way the corner points are always steady and reliable when a vehicle is steering and moving, or the camera is zooming in/out, and the tracking algorithm proposed can provide an accurate and real-time match for the feature points.