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.
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