Computation of Optical Flow using Dynamic

This paper presents an original algorithm for the computation of optical ow called Orthogonal Dynamic Programming (ODP) as well as several enhancements to it. The principle is to minimize a sum of square diierences (SSD) between a pair of images. The originality of the approach is that an optimal matching is searched for entire image strips rather than for pixel neighborhoods. Dynamic programming is used to provide very robust strip alignments and a multiresolution iterative process is used to compute the velocity eld. Extensions to the computation of the velocity eld for non integer image indexes, to the use of more than two images, and to the search for subpixel velocities, are presented. Results obtained for the Barron, Fleet and Beauchemin performance tests appear to be at least as good as or better than those obtained using classical optical ow detection methods.

[1]  B. Zavidovique,et al.  Pattern Recognition Through Dynamic Programming , 1985, Optics & Photonics.

[2]  QU GeorgesM IMAGE MATCHING USING DYNAMIC PROGRAMMING APPLICATION TO STEREOVISION AND IMAGE INTERPOLATION , 1996 .

[3]  Takeo Kanade,et al.  Stereo by Intra- and Inter-Scanline Search Using Dynamic Programming , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  B. Zavidovique,et al.  Dynamic programming for region based pattern recognition , 1986, ICASSP '86. IEEE International Conference on Acoustics, Speech, and Signal Processing.

[5]  G. M. Quenot The 'orthogonal algorithm' for optical flow detection using dynamic programming , 1992, [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing.