ML Anthology

Affine Invariance Revisited

Evgeni Begelfor, Michael Werman
CVPR 2006 pp. 2087-2094
doi:10.1109/CVPR.2006.50 /cvpr/2006/begelfor2006cvpr-affine/

Abstract

This paper proposes a Riemannian geometric framework to compute averages and distributions of point configurations so that different configurations up to affine transformations are considered to be the same. The algorithms are fast and proven to be robust both theoretically and empirically. The utility of this framework is shown in a number of affine invariant clustering algorithms on image point data.

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Cite

Text

Begelfor and Werman. "Affine Invariance Revisited." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2006. doi:10.1109/CVPR.2006.50

Markdown

[Begelfor and Werman. "Affine Invariance Revisited." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2006.](https://mlanthology.org/cvpr/2006/begelfor2006cvpr-affine/) doi:10.1109/CVPR.2006.50

BibTeX

@inproceedings{begelfor2006cvpr-affine,
  title     = {{Affine Invariance Revisited}},
  author    = {Begelfor, Evgeni and Werman, Michael},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2006},
  pages     = {2087-2094},
  doi       = {10.1109/CVPR.2006.50},
  url       = {https://mlanthology.org/cvpr/2006/begelfor2006cvpr-affine/}
}