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A census-based stereo vision algorithm using modified Semi-Global Matching and plane fitting to improve matching quality
2010
2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops
This paper introduces a new segmentation-based approach for disparity optimization in stereo vision. The main contribution is a significant enhancement of the matching quality at occlusions and textureless areas by segmenting either the left color image or the calculated texture image. The local cost calculation is done with a Census-based correlation method and is compared with standard sum of absolute differences. The confidence of a match is measured and only non-confident or non-textured
doi:10.1109/cvprw.2010.5543769
dblp:conf/cvpr/HumenbergerEK10
fatcat:a47d4gz6xrc3vnokq55trhodfq