Abstract
Optical flow or image motion estimation is important in the area of computer vision. This paper presents a fast and reliable optical flow algorithm which produces a dense optical flow map by using fast cross-correlation and shortest-path techniques. Fast correlation is achieved by using the box filtering technique which is invariant to the size of the correlation window. The motion for each scan line of the input image is obtained from the correlation volume by finding the best 3D path using dynamic programming rather than simply choosing the position that gives the maximum cross correlation coefficient. Sub-pixel accuracy is achieved by fitting the local correlation coefficients to a quadratic surface. Typical running time for a 256\Theta256 image is in the order of a few seconds rather than minutes. A variety of synthetic and real images have been tested, and good results have been obtained. 1. Introduction Optical flow or image motion is the displacement of each image pixels in an...
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