Ordinal Measures for Visual Correspondence (1997)
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| Venue: | In IEEE Conference on Computer Vision and Pattern Recognition |
| Citations: | 23 - 3 self |
BibTeX
@INPROCEEDINGS{Bhat97ordinalmeasures,
author = {Dinkar N. Bhat and Dinkar N. Bhat and Shree K. Nayar and Shree K. Nayar},
title = {Ordinal Measures for Visual Correspondence},
booktitle = {In IEEE Conference on Computer Vision and Pattern Recognition},
year = {1997},
pages = {351--357}
}
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Abstract
We present ordinal measures of association for establishing visual correspondence in images. Linear correspondence measures like correlation and the sum of squared differences are known to be fragile. Ordinal measures, which are based on relative ordering of intensity values in windows, have demonstrable robustness to depth discontinuities, occlusion, and noise. The relative ordering of intensity values in each window is represented by a rank permutation which is obtained by sorting the corresponding intensity data. By using distance metrics between the rank permutations of windows, ordinal correlation coefficients can be arrived at. These coefficients are independent of absolute intensity scale, i.e they are normalized measures. Further, since rank permutations are invariant to monotone transformations of the intensity values, the coefficients are unaffected by nonlinear effects like gamma variation between images. We discuss two crucial properties of ordinal measures for stereo appli...
