A hybrid genetic approach for stereo matching | Zendy

Eliyahu Kiperwasser | Zendy; Omid E. David | Zendy; Nathan S. Netanyahu | Zendy

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A hybrid genetic approach for stereo matching

Author(s) -

Eliyahu Kiperwasser,

Omid E. David,

Nathan S. Netanyahu

Publication year - 2013

Publication title -

citeseer x (the pennsylvania state university)

Language(s) - English

Resource type - Conference proceedings

DOI - 10.1145/2463372.2463542

Subject(s) - benchmark (surveying) , matching (statistics) , scheme (mathematics) , computer science , genetic programming , genetic algorithm , simple (philosophy) , dynamic programming , artificial intelligence , algorithm , mathematical optimization , computer vision , pattern recognition (psychology) , mathematics , machine learning , statistics , mathematical analysis , philosophy , geodesy , epistemology , geography

In this paper we present a genetic algorithm (GA)-based approach for the stereo matching problem. More precisely, the approach presented is a combination of a simple dynamic programming algorithm, commonly used for stereo matching, with a practical GA-based optimization scheme. The performance of our scheme was evaluated on standard test data of the Middlebury benchmark. Specifically, the number of incorrect disparities on these data decreases by approximately 20% in comparison to the original approach (without the use of a GA).

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