The Middlebury Stereo Vision homepage provides results and evaluation code for comparing dense two frame stereo correlation algorithms. As well as providing a wealth of standard datasets with ground truth data the top ranking correlation algorithms are compared and evaluated for weaknesses. Finally Middlebury provide a comprehensive c++ stereo matching framework for comparing newly implemented correlation algorithms against other state of the art solutions. The home page, data and framework combine to support the work presented in Daniel Scharstein and Richard Szeliski’s 2001 paper: “A taxonomy and evaluation of dense two-frame stereo correspondence algorithms“. [pdf]
Middlebury provide the following useful material on their site:
- An on-line evaluation of current algorithms
- Many stereo datasets with ground-truth disparities
- Stereo correspondence software
- An on-line submission script that allows you to evaluate your stereo algorithm in their framework