A taxonomy and evaluation of dense two-frame stereo correspondence algorithms Export

@proceedings{citeulike:126702, 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, two-frame 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 the performance of many different variants. In order to establish a common software platform and a collection of data sets for easy evaluation, we have designed a stand-alone, flexible C++ implementation that enables the evaluation of individual components and that can be easily extended to include new algorithms. We have also produced several new multiframe stereo data sets with ground truth, and are making both the code and data sets available on the Web}, author = {Scharstein, D. and Szeliski, R. and Zabih, R.}, citeulike-article-id = {126702}, citeulike-linkout-0 = {http://dx.doi.org/10.1109/SMBV.2001.988771}, citeulike-linkout-1 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=988771}, doi = {10.1109/SMBV.2001.988771}, journal = {Stereo and Multi-Baseline Vision, 2001. (SMBV 2001). Proceedings. IEEE Workshop on}, keywords = {stereo}, pages = {131--140}, posted-at = {2008-02-25 17:14:27}, priority = {2}, title = {A taxonomy and evaluation of dense two-frame stereo correspondence algorithms}, url = {http://dx.doi.org/10.1109/SMBV.2001.988771}, year = {2001} }

TY - CONF ID - citeulike:126702 L3 - citeulike-article-id:126702 N2 - 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, two-frame 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 the performance of many different variants. In order to establish a common software platform and a collection of data sets for easy evaluation, we have designed a stand-alone, flexible C++ implementation that enables the evaluation of individual components and that can be easily extended to include new algorithms. We have also produced several new multiframe stereo data sets with ground truth, and are making both the code and data sets available on the Web JF - Stereo and Multi-Baseline Vision, 2001. (SMBV 2001). Proceedings. IEEE Workshop on EP - 140 TI - A taxonomy and evaluation of dense two-frame stereo correspondence algorithms SP - 131 KW - stereo AU - Scharstein, D AU - Szeliski, R AU - Zabih, R PY - 2001/// UR - http://dx.doi.org/10.1109/SMBV.2001.988771 ER -