Optimum displacement estimates using mean field annealing

Ikhlas M. Abdelqader; Sarah A. Rajala; Griff L. Bilbro; Wesley E. Snyder

doi:10.1117/12.146685

10 June 1993 Optimum displacement estimates using mean field annealing

Ikhlas M. Abdelqader, Sarah A. Rajala, Griff L. Bilbro, Wesley E. Snyder

Proceedings Volume 1904, Image Modeling; (1993) https://doi.org/10.1117/12.146685
Event: IS&T/SPIE's Symposium on Electronic Imaging: Science and Technology, 1993, San Jose, CA, United States

Abstract

In this paper a new algorithm to estimate dense displacement fields from a sequence of images is developed. The algorithm is based on modeling the displacement fields as Markov Random fields. The Markov Random fields-Gibbs equivalence is then used to convert the problem into one of finding an appropriate energy function that describes the motion and any constraints imposed on it. Mean field annealing, a technique which finds global minima in nonconvex optimization problems, is used to minimize the energy function, and solve for the optimum displacement fields. The algorithm results in accurate estimates even for scenes with noise or discontinuities.

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Ikhlas M. Abdelqader, Sarah A. Rajala, Griff L. Bilbro, and Wesley E. Snyder "Optimum displacement estimates using mean field annealing", Proc. SPIE 1904, Image Modeling, (10 June 1993); https://doi.org/10.1117/12.146685

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