A Stereo Matching Algorithm with an Adaptive Window: Theory and Experiment

Takeo Kanade and M. Okutomi
Proceedings of the 1991 IEEE International Conference on Robotics and Automation (ICRA '91), April, 1991, pp. 1088-1095.


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Abstract
An iterative stereo matching algorithm is presented which selects a window adaptively for each pixel. The selected window is optimal in the sense that it produces the disparity estimate having the least uncertainty after evaluating both the intensity and the disparity variations within a window. The algorithm employs a statistical model that represents uncertainty of disparity of points over the window; the uncertainty is assumed to increase with the distance of the point from the center point. The algorithm is completely local and does not include any global optimization. Also, the algorithm does not use any post-processing smoothing, but smooth surfaces are recovered as smooth while sharp disparity edges are retained. Experimental results have demonstrated a clear advantage of this algorithm over algorithms with a fixed-size window, for both synthetic and real images.

Notes
Associated Center(s) / Consortia: Vision and Autonomous Systems Center

Text Reference
Takeo Kanade and M. Okutomi, "A Stereo Matching Algorithm with an Adaptive Window: Theory and Experiment," Proceedings of the 1991 IEEE International Conference on Robotics and Automation (ICRA '91), April, 1991, pp. 1088-1095.

BibTeX Reference
@inproceedings{Kanade_1991_2449,
   author = "Takeo Kanade and M. Okutomi",
   title = "A Stereo Matching Algorithm with an Adaptive Window: Theory and Experiment",
   booktitle = "Proceedings of the 1991 IEEE International Conference on Robotics and Automation (ICRA '91)",
   pages = "1088-1095",
   month = "April",
   year = "1991",
   volume = "2",
}