Classification and performance evaluation of different aggregation costs for stereo matching
Federico Tombari • Stefano Mattoccia • Luigi Di Stefano • Elisa Addimanda
Proposed methodology and evaluation
We have been studying a classification and performance evaluation methodology of aggregation strategies which have been proposed so far in literature for the stereo matching problem [1]. In the last decades several cost aggregation methods aimed at improving the robustness of stereo correspondence within local and global algorithms have been proposed. Given the recent developments and the lack of an appropriate comparison, we have been surveying, classifying and comparing experimentally on a standard data set the main cost aggregation approaches proposed in literature. Preliminary results of this work appear in [1]. In this web page, we propose preliminary results dealing with our experimental evaluation, which addresses both accuracy and computational requirements. The proposed experimental results are done using the stereo pairs of the Middlebury Stereo Evaluation dataset [2]
References
| [1] | F. Tombari, S. Mattoccia, L. Di Stefano, E. Addimanda, “Classification and evaluation of cost aggregation methods for stereo correspondence", IEEE International Conference on Computer Vision and Pattern Recognition (CVPR 2008), 2008. |
| [2] | D. Scharstein and R. Szeliski, "A taxonomy and evaluation of dense two-frame stereo correspondence algorithms", Int. Journal Computer Vision, 2002. |
Last modified: July 10 2008