Merit maximization approach to binocular vision using dynamic programming

Suya ok You; Jian Liu; Faguang Wan

doi:10.1117/12.139105

12 January 1993 Merit maximization approach to binocular vision using dynamic programming

Suya ok You, Jian Liu, Faguang Wan

Author Affiliations +

Proceedings Volume 1771, Applications of Digital Image Processing XV; (1993) https://doi.org/10.1117/12.139105
Event: San Diego '92, 1992, San Diego, CA, United States

Abstract

In this paper, wp cast stereo matching as a problem in merit maximization. This is achieved by the formulation of a merit function which influence the similarity between primitives in the right and left images and the mutual dependency between primitives. Stereo matching are done by finding the "best" paths that maximize the merit function. This is handled by using dynamic programming technique. With this algorithm, a global optimum matching can be obtained. We give a mathematical description for the merit function and the algorithm has been implemented. The experimental results are presented to show the efficacy of the proposed stereo matching method.

Citation Download Citation

Suya ok You, Jian Liu, and Faguang Wan "Merit maximization approach to binocular vision using dynamic programming", Proc. SPIE 1771, Applications of Digital Image Processing XV, (12 January 1993); https://doi.org/10.1117/12.139105

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