Stereo Correspondence with Compact Windows via Minimum Ratio Cycle
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Radial Cumulative Similarity Transform for Robust Image Correspondence
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Stereo Computation Using Radial Adaptive Windows
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
Adaptive Support-Weight Approach for Correspondence Search
IEEE Transactions on Pattern Analysis and Machine Intelligence
Segmentation-based adaptive support for accurate stereo correspondence
PSIVT'07 Proceedings of the 2nd Pacific Rim conference on Advances in image and video technology
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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In this paper, we propose a new stereo matching method using pixel cooperative optimization. First, we modify adaptive support weights to achieve constant time O(1) regardless of the window size. To obtain more accurate results, we refine our results using pixel cooperation at each window. Even though our refining process requires some additional computational costs, we are able to keep them minimum by using CUDA. Our experimental results show that the accuracy of the generated depth map is as good as the ones suggested by recent methods but the computational cost is less than these ones.