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A Computational Approach to Steerable Functions

Patrick C. Teo, Yacov Hel-Or
CVPR 1997 pp. 313-318
doi:10.1109/CVPR.1997.609341 /cvpr/1997/teo1997cvpr-computational/

Abstract

We present a computational, group-theoretic approach to steerable functions. The approach is group-theoretic in that the treatment involves continuous transformation groups for which elementary Lie group theory may be applied. The approach is computational in that the theory is constructive and leads directly to a procedural implementation. For functions that are steerable with n finite number of basis functions under a k-parameter group, the procedure is efficient and is guaranteed to return the minimum number of basis functions. If the function is not steerable, a numerical implementation of the procedure could also be used to compute basis functions that approximately steer the function over a range of transformation parameters. Examples of both applications are demonstrated.

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Cite

Text

Teo and Hel-Or. "A Computational Approach to Steerable Functions." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1997. doi:10.1109/CVPR.1997.609341

Markdown

[Teo and Hel-Or. "A Computational Approach to Steerable Functions." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1997.](https://mlanthology.org/cvpr/1997/teo1997cvpr-computational/) doi:10.1109/CVPR.1997.609341

BibTeX

@inproceedings{teo1997cvpr-computational,
  title     = {{A Computational Approach to Steerable Functions}},
  author    = {Teo, Patrick C. and Hel-Or, Yacov},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1997},
  pages     = {313-318},
  doi       = {10.1109/CVPR.1997.609341},
  url       = {https://mlanthology.org/cvpr/1997/teo1997cvpr-computational/}
}