A Bayesian approach to binocular stereopsis
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Stereo Matching with Nonlinear Diffusion
International Journal of Computer Vision
Stereo Matching with Transparency and Matting
International Journal of Computer Vision - 1998 Marr Prize
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Stereo Matching Algorithm with an Adaptive Window: Theory and Experiment
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Cooperative Algorithm for Stereo Matching and Occlusion Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Occlusions and Binocular Stereo
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Occlusions, Discontinuities, and Epipolar Lines in Stereo
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Robust analysis of feature spaces: color image segmentation
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Occlusion Detectable Stereo -- Occlusion Patterns in Camera Matrix
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Markov Random Fields with Efficient Approximations
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
A multibaseline stereo system with active illumination and real-time image acquisition
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
SMBV '01 Proceedings of the IEEE Workshop on Stereo and Multi-Baseline Vision (SMBV'01)
A Maximum-Flow Formulation of the N-Camera Stereo Correspondence Problem
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 2
Neural adaptive stereo matching
Pattern Recognition Letters
Stereo Using Monocular Cues within the Tensor Voting Framework
IEEE Transactions on Pattern Analysis and Machine Intelligence
Stereo Correspondence with Occlusion Handling in a Symmetric Patch-Based Graph-Cuts Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Neural disparity computation for dense two-frame stereo correspondence
Pattern Recognition Letters
A People Counting System Based on Dense and Close Stereovision
ICISP '08 Proceedings of the 3rd international conference on Image and Signal Processing
A Stereo Depth Recovery Method Using Layered Representation of the Scene
Proceedings of the 31st DAGM Symposium on Pattern Recognition
Obtaining depth map from segment-based stereo matching using graph cuts
Journal of Visual Communication and Image Representation
Feature-based 3-D surface reconstruction directed by grid space projection
ICAI'05/MCBC'05/AMTA'05/MCBE'05 Proceedings of the 6th WSEAS international conference on Automation & information, and 6th WSEAS international conference on mathematics and computers in biology and chemistry, and 6th WSEAS international conference on acoustics and music: theory and applications, and 6th WSEAS international conference on Mathematics and computers in business and economics
Efficient disparity estimation using region based segmentation and multistage feedback
ICCOM'06 Proceedings of the 10th WSEAS international conference on Communications
On Learning Conditional Random Fields for Stereo
International Journal of Computer Vision
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In this paper we present a new stereo matching algorithm that produces accurate dense disparity maps and explicitly detects occluded areas. This algorithm extends the original cooperative algorithms in two ways. First, we design a method of adjusting the initial matching score volume to guarantee that correct matches have high matching scores. This method propagates "good" disparity information within or among image segments based on certain disparity confidence measurement criterion, thus improving the robustness of the algorithm. Second, we develop a scheme of choosing local support areas by enforcing the image segmentation information. This scheme sees that the depth discontinuities coincide with the color or intensity boundaries. As a result, the foreground fattening errors are drastically reduced. Extensive experimental results demonstrate the effectiveness of our algorithm, both quantitatively and qualitatively. Comparison between our algorithm and some other representative algorithms is also reported.