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2008
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Towards estimation of dense disparities from stereo images containing large textureless regions

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Towards estimation of dense disparities from stereo images containing large textureless regions
Stereo algorithms for structure reconstruction demand accurate disparities with low mismatch errors and false positives. Mismatch errors in large textureless regions force most accurate algorithms to be sparse, with disparities known only in textured regions. We propose a novel method which uses characteristics of the multi-valued disparity to segregate image regions into unambiguous, occluded but textured and regions with low color variation. The disparity in the unambiguous region is calculated using stable matching with local disparity filtering. The disparity is interpolated into other regions by diffusion using unstructured triangulation and method of finite elements for rapid convergence. The boundary conditions for each of the region are appropriately modified so that accurate discontinuities in the disparity are preserved. A comparison of our method with some existing methods through experiments reveal that this algorithm indeed performs significantly better in...
Rohith MV, Gowri Somanath, Chandra Kambhamettu, Ca
Added 09 Nov 2010
Updated 09 Nov 2010
Type Conference
Year 2008
Where ICPR
Authors Rohith MV, Gowri Somanath, Chandra Kambhamettu, Cathleen Geiger
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