Fast Motion Estimation

Optical flow estimation is important in the area of computer vision. This paper presents a fast and reliable approach for robust boundary preserving estimation of optical flow. Variational approaches have addressed this topic and proposed methods that account for velocity boundaries at the cost of significant computational complexity, which makes them inadequate for current real-time applications. The proposed method is derived from the benchmark algorithm of Horn & Schunck and Simoncelli's matched-pair 5 tap filters, such that it produces robust, fast and exact detection of motion boundaries and it is very simple to implement. A variety of synthetic and real images have been tested, and good results have been obtained.