Cited By
View all- Dinh VNguyen VVan Nguyen HJeon J(2016)Fuzzy Encoding Pattern for Stereo Matching CostIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2015.245573126:7(1215-1228)Online publication date: 7-Jul-2016
Fast and robust semi-local stereo matching using possibility distributions
Pages 237 - 253
Abstract
Global stereo matching methods aim to reduce the sensibility of stereo correspondence to ambiguities caused by occlusions, poor local texture or fluctuation of illumination. However, when facing the problem of real-time stereo matching, as in robotic vision, local algorithms are known to be the best. In this paper, we propose a semi-local stereo matching algorithm (SLSM algorithm); an area-based method that embodies global matching constraints in the matching score. Our approach uses a fuzzy formularisation of the similarity assumption in order to define a matching possibility distribution. An unmatching possibility distribution is defined by applying global constraints to the matching possibility distribution. The final matching cost is computed using the two possibility distributions. Experimental results and comparison with other existing algorithms are presented to demonstrate the performance and effectiveness of our approach.
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- Fast and robust semi-local stereo matching using possibility distributions
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Published: 01 October 2011
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View all- Dinh VNguyen VVan Nguyen HJeon J(2016)Fuzzy Encoding Pattern for Stereo Matching CostIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2015.245573126:7(1215-1228)Online publication date: 7-Jul-2016