ML Anthology

3D Shape Matching by Geodesic Eccentricity

Adrian Ion, Nicole M. Artner, Gabriel Peyré, Salvador B. López Mármol, Walter G. Kropatsch, Laurent D. Cohen
CVPRW 2008 pp. 1-8
doi:10.1109/CVPRW.2008.4563032 /cvprw/2008/ion2008cvprw-3d/

Abstract

This paper makes use of the continuous eccentricity transform to perform 3D shape matching. The eccentricity transform has already been proved useful in a discrete graph-theoretic setting and has been applied to 2D shape matching. We show how these ideas extend to higher dimensions. The eccentricity transform is used to compute descriptors for 3D shapes. These descriptors are defined as histograms of the eccentricity transform and are naturally invariant to Euclidean motion and articulation. They show promising results for shape discrimination.

PDF CVPRW Semantic Scholar

Cite

Text

Ion et al. "3D Shape Matching by Geodesic Eccentricity." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2008. doi:10.1109/CVPRW.2008.4563032

Markdown

[Ion et al. "3D Shape Matching by Geodesic Eccentricity." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2008.](https://mlanthology.org/cvprw/2008/ion2008cvprw-3d/) doi:10.1109/CVPRW.2008.4563032

BibTeX

@inproceedings{ion2008cvprw-3d,
  title     = {{3D Shape Matching by Geodesic Eccentricity}},
  author    = {Ion, Adrian and Artner, Nicole M. and Peyré, Gabriel and Mármol, Salvador B. López and Kropatsch, Walter G. and Cohen, Laurent D.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2008},
  pages     = {1-8},
  doi       = {10.1109/CVPRW.2008.4563032},
  url       = {https://mlanthology.org/cvprw/2008/ion2008cvprw-3d/}
}