A hybrid genetic approach for stereo matching

Eliyahu Kiperwasser, Omid David, Nathan S. Netanyahu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

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 [1]. 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).

Original languageEnglish
Title of host publicationGECCO 2013 - Proceedings of the 2013 Genetic and Evolutionary Computation Conference
Pages1325-1331
Number of pages7
DOIs
StatePublished - 2013
Event2013 15th Genetic and Evolutionary Computation Conference, GECCO 2013 - Amsterdam, Netherlands
Duration: 6 Jul 201310 Jul 2013

Publication series

NameGECCO 2013 - Proceedings of the 2013 Genetic and Evolutionary Computation Conference

Conference

Conference2013 15th Genetic and Evolutionary Computation Conference, GECCO 2013
Country/TerritoryNetherlands
CityAmsterdam
Period6/07/1310/07/13

Keywords

  • Computer vision
  • Genetic algorithm
  • Stereo matching

Fingerprint

Dive into the research topics of 'A hybrid genetic approach for stereo matching'. Together they form a unique fingerprint.

Cite this