Intrinsic Stabilizers of Planar Curves
Abstract
Regularization offers a powerful framework for signal reconstruction by enforcing weak constraints through the use of stabilizers. Stabilizers are functionals measuring the degree of smoothness of a surface. The nature of those functionals constrains the properties of the reconstructed signal. In this paper, we first analyze the invariance of stabilizers with respect to size, transformation and their ability to control scale at which the smoothness is evaluated. Tikhonov stabilizers are widely used in computer vision, even though they do not incorporate any notion of scale and may result in serious shape distortion. We first introduce an extension of Tikhonov stabilizers that offers natural scale control of regularity. We then introduce the intrinsic stabilizers for planar curves that apply smoothness constraints on the curvature profile instead of the parameter space.
Cite
Text
Delingette. "Intrinsic Stabilizers of Planar Curves." European Conference on Computer Vision, 1994. doi:10.1007/BFB0028374Markdown
[Delingette. "Intrinsic Stabilizers of Planar Curves." European Conference on Computer Vision, 1994.](https://mlanthology.org/eccv/1994/delingette1994eccv-intrinsic/) doi:10.1007/BFB0028374BibTeX
@inproceedings{delingette1994eccv-intrinsic,
title = {{Intrinsic Stabilizers of Planar Curves}},
author = {Delingette, Herve},
booktitle = {European Conference on Computer Vision},
year = {1994},
pages = {427-436},
doi = {10.1007/BFB0028374},
url = {https://mlanthology.org/eccv/1994/delingette1994eccv-intrinsic/}
}