TY - GEN
T1 - A hybrid genetic approach for stereo matching
AU - Kiperwasser, Eliyahu
AU - David, Omid
AU - Netanyahu, Nathan S.
PY - 2013
Y1 - 2013
N2 - 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).
AB - 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).
KW - Computer vision
KW - Genetic algorithm
KW - Stereo matching
UR - http://www.scopus.com/inward/record.url?scp=84883074227&partnerID=8YFLogxK
U2 - 10.1145/2463372.2463542
DO - 10.1145/2463372.2463542
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AN - SCOPUS:84883074227
SN - 9781450319638
T3 - GECCO 2013 - Proceedings of the 2013 Genetic and Evolutionary Computation Conference
SP - 1325
EP - 1331
BT - GECCO 2013 - Proceedings of the 2013 Genetic and Evolutionary Computation Conference
T2 - 2013 15th Genetic and Evolutionary Computation Conference, GECCO 2013
Y2 - 6 July 2013 through 10 July 2013
ER -