A Pixel Dissimilarity Measure That Is Insensitive to Image Sampling
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
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
Dense Structure-from-Motion: An Approach Based on Segment Matching
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
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
Advances in Computational Stereo
IEEE Transactions on Pattern Analysis and Machine Intelligence
What Energy Functions Can Be Minimizedvia Graph Cuts?
IEEE Transactions on Pattern Analysis and Machine Intelligence
High-quality video view interpolation using a layered representation
ACM SIGGRAPH 2004 Papers
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
A Symmetric Patch-Based Correspondence Model for Occlusion Handling
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Stereo analysis by hybrid recursive matching for real-time immersive video conferencing
IEEE Transactions on Circuits and Systems for Video Technology
An asymmetric post-processing for correspondence problem
Image Communication
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In this paper, we propose a new stereo matching algorithm using an iterated graph cuts and mean shift filtering technique. Our algorithm estimates the disparity map progressively through the following two steps. In the first step, with a previously estimated RDM (reliable disparity map) that consists of sparse ground control points, an updated dense disparity map is constructed through a RDM constrained energy minimization framework that can cope with occlusion. The graph cuts technique is employed for the solution of the proposed energy model. In the second step, more accurate and denser RDM is estimated through the disparity crosschecking technique and the mean shift filtering in the CSD (color-spatial-disparity) space. The proposed algorithm expands the reliable disparities in RDM repeatedly through the above two steps until it converges. Experimental results on the standard data set demonstrate that the proposed algorithm achieves comparable performance to the state-of-the-arts, and gives excellent results especially in the areas such as the disparity discontinuous boundaries and occluded regions, where the conventional methods usually suffer.