Abstract
Real-time stereo matching is necessary for many practical applications, including robotics. There are already many real-time stereo systems, but they typically use local approaches that cause object boundaries to be blurred and small objects to be removed. We have selected the Semi-Global Matching (SGM) method for implementation on graphics hardware, because it can compete with the currently best global stereo methods. At the same time, it is much more efficient than most other methods that produce a similar quality. In contrast to previous work, we have fully implemented SGM including matching with mutual information, which is partly responsible for the high quality of disparity images. Our implementation reaches 4.2 fps on a GeForce 8800 ULTRA with images of 640 ×480 pixel size and 128 pixel disparity range and 13 fps on images of 320 ×240 pixel size and 64 pixel disparity range.
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Ernst, I., Hirschmüller, H. (2008). Mutual Information Based Semi-Global Stereo Matching on the GPU. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2008. Lecture Notes in Computer Science, vol 5358. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89639-5_22
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DOI: https://doi.org/10.1007/978-3-540-89639-5_22
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