Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.jvcir.2011.02.001
Title: Obtaining depth map from segment-based stereo matching using graph cuts
Authors: Wang, D.
Lim, K.B. 
Keywords: Clustering
Color segmentation
Disparity plane fitting
Graph cuts
Occlusion
Optimization
Similarity measure
Stereo matching
Issue Date: May-2011
Source: Wang, D., Lim, K.B. (2011-05). Obtaining depth map from segment-based stereo matching using graph cuts. Journal of Visual Communication and Image Representation 22 (4) : 325-331. ScholarBank@NUS Repository. https://doi.org/10.1016/j.jvcir.2011.02.001
Abstract: In the paper, the algorithm of segment-based stereo matching using graph cuts is developed for extracting depth information from the stereo image pairs. The first step of the algorithm employs the mean-shift algorithm to segment the reference image, which ensures our method to correctly estimate in large untextured regions and precisely localize depth boundaries, followed by the use of Adaptive Support Weighted Self-Adaptation dissimilarity algorithm (ASW-SelfAd) for the estimation of initial disparity. This is followed by application of Singular Value Decomposition (SVD) in solving the robust disparity plane fitting. In order to ensure reliable pixel sets for the segment, we filter out outliers which contain occlusion region through three main rules, namely; cross-checking, judging reliable area and disparity distance measurement. Lastly, we apply improved clustering algorithm to merge the neighboring segments. The geometrical relationship of adjacent planes such as parallelism and intersection is employed for determination of whether two planes shall be merged. A new energy function is subsequently formulated with the use of graph cuts for the refinement of the disparity map. Finally, the depth information is extracted from the final disparity map. Experimental results on the Middlebury dataset demonstrate that our approach is effective in improving the state of the art. © 2011 Elsevier Inc. All rights reserved.
Source Title: Journal of Visual Communication and Image Representation
URI: http://scholarbank.nus.edu.sg/handle/10635/60975
ISSN: 10473203
DOI: 10.1016/j.jvcir.2011.02.001
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