A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Stereo Matching with Nonlinear Diffusion
International Journal of Computer Vision
International Journal of Computer Vision
Fast Approximate Energy Minimization via Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
Stereo Matching Using Belief Propagation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computing Visual Correspondence with Occlusions via Graph Cuts
Computing Visual Correspondence with Occlusions via Graph Cuts
Depth Discontinuities by Pixel-to-Pixel Stereo
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
A Dense Stereo Matching Using Two-Pass Dynamic Programming with Generalized Ground Control Points
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Fast variable window for stereo correspondence using integral images
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
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Local stereo correspondence is usually not satisfactory because neither big window nor small window based methods can accurately match densely-textured and textureless regions at the same time. In this paper, we present a progressive edge-based stereo matching algorithm, in which big window and small window based matches are progressively integrated based on the edges of disparity map of a big window based matching. In addition, an arbitrarily-shaped window based matching is used for the regions where big windows and small windows can not find matches, and a novel optimization method, progressive outlier remover, is used to effectively remove outliers and noise. Empirical results show that our method is comparable to some state-of-the-art stereo correspondence algorithms.