Motion vehicle tracking based on multi-resolution optical flow and multi-scale Harris corner detection

Multi-resolution optical flow tracking algorithm based on wavelet pyramid is proposed by analyzing the limitations of sparse optical flow based on LK (lucas-kanade) algorithm. The problem that LK algorithm cannot steadily track rapid motion objects by LK algorithm is solved. According to the feature of motion vehicles, multi-scale Harris corner detection based on wavelet is proposed. The problem of limitation of Traditional Harris corner detection about omitting corner point and asymmetrical array is solved. It is suitable to extract motion vehicle feature in complicated traffic scene. Experimentation result shows that the corner point is always steady and reliable when the vehicle is rotating and moving, and the camera is zooming in and out. The tracking algorithm also can accurately match the feature points with the high real-time performance.