A Pixel Dissimilarity Measure That Is Insensitive to Image Sampling
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Approximate Energy Minimization via Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
Multi-camera Scene Reconstruction via Graph Cuts
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Stereo Matching Using Belief Propagation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Comparison of Graph Cuts with Belief Propagation for Stereo, using Identical MRF Parameters
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Symmetric Stereo Matching for Occlusion Handling
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
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
Stereo Using Monocular Cues within the Tensor Voting Framework
IEEE Transactions on Pattern Analysis and Machine Intelligence
Surface Geometric Constraints for Stereo in Belief Propagation
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Segment-Based Stereo Matching Using Belief Propagation and a Self-Adapting Dissimilarity Measure
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
A comparative study of energy minimization methods for markov random fields
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
Surfaces with occlusions from layered stereo
IEEE Transactions on Pattern Analysis and Machine Intelligence
Occlusion filling in stereo: Theory and experiments
Computer Vision and Image Understanding
Depth sculpturing for 2D paintings: A progressive depth map completion framework
Journal of Visual Communication and Image Representation
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We decompose the stereo matching problem into three sub-problems in this work: (1) disparity estimation for non-occlusion regions and occlusion detection, (2) disparity estimation for occlusion regions, and (3) surface model for the disparity map. A three-step procedure is proposed to solve them sequentially. At the first step, we perform an initial matching and develop a new graph model using the ordering and segmentation constraints to improve disparity values in non-occlusion regions and detect occlusion regions. At the second step, we determine disparity values in occlusion regions based on global optimization. Since the conventional segmentation-based stereo matching is not efficient in highly slanted or curved objects, we propose a post-processing technique for disparity map enhancement using a three-dimensional (3D) geometric structure. The proposed three-step stereo matching procedure yields excellent quantitative and qualitative results with Middlebury data sets.