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Abstract: Stereo matching is one of the most active research areas in computer vision. While a large number of algorithms for stereo correspondence have been developed, relatively little work has been done on characterizing their performance. In this paper; we present a taxonomy of dense, twoframe stereo methods designed to assess the different components and design decisions made in individual stereo algorithms. Using this taxonomy, we compare existing stereo methods and present experiments evaluating... (Update)
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BibTeX entry: (Update)
Daniel Scharstein, Richard Szeliski, and Ramin Zabih. A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. In Proceedings of the IEEE Workshop on Stereo and Multi-Baseline Vision, Kauai, HI, Dec. 2001. http://citeseer.ist.psu.edu/article/scharstein01taxonomy.html More
@misc{ scharstein01taxonomy,
author = "D. Scharstein and R. Szeliski and R. Zabih",
title = "A taxonomy and evaluation of dense two-frame stereo correspondence algorithms",
text = "Daniel Scharstein, Richard Szeliski, and Ramin Zabih. A taxonomy and evaluation
of dense two-frame stereo correspondence algorithms. In Proceedings of the
IEEE Workshop on Stereo and Multi-Baseline Vision, Kauai, HI, Dec. 2001.",
year = "2001",
url = "citeseer.ist.psu.edu/article/scharstein01taxonomy.html" }
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Documents on the same site (http://community.middlebury.edu/~schar/pubs.html):
A Taxonomy and Evaluation of Dense Two-Frame Stereo.. - Scharstein, Szeliski (2001) (Correct)
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