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Daniel ScharsteinRichard SzeliskiHeiko Hirschmüller

Welcome to the Middlebury Stereo Vision Page. This website accompanies our taxonomy and comparison of two-frame stereo correspondence algorithms [1], extending our initial paper with Ramin Zabih [2]. It contains: How to cite the materials on this website:
We grant permission to use and publish all images and numerical results on this website. If you report performance results, we request that you cite our paper [1]. Instructions on how to cite our datasets are listed on the datasets page. If you want to cite this website, please use the URL "vision.middlebury.edu/stereo/".

References:
[1] D. Scharstein and R. Szeliski. A taxonomy and evaluation of dense two-frame stereo correspondence algorithms.
International Journal of Computer Vision, 47(1/2/3):7-42, April-June 2002.
Microsoft Research Technical Report MSR-TR-2001-81, November 2001.
[2] D. Scharstein, R. Szeliski, and R. Zabih. A taxonomy and evaluation of dense two-frame stereo correspondence algorithms.
In Workshop on Stereo and Multi-Baseline Vision (in conjunction with IEEE CVPR 2001), pages 131-140, Kauai, Hawaii, December 2001.

 


Other online stereo benchmarks:

 

 

 

Support for this work was provided in part by NSF CAREER grant 9984485 and NSF grant IIS-0413169. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

 

 

 

 

 

 

 

 

 

 

Last modified: May 1 2023 by Daniel Scharstein