ML Anthology

Shape Google: A Computer Vision Approach to Isometry Invariant Shape Retrieval

Maks Ovsjanikov, Alexander M. Bronstein, Michael M. Bronstein, Leonidas J. Guibas
ICCVW 2009 pp. 320-327
doi:10.1109/ICCVW.2009.5457682 /iccvw/2009/ovsjanikov2009iccvw-shape/

Abstract

Feature-based methods have recently gained popularity in computer vision and pattern recognition communities, in applications such as object recognition and image retrieval. In this paper, we explore analogous approaches in the 3D world applied to the problem of non-rigid shape search and retrieval in large databases.

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Cite

Text

Ovsjanikov et al. "Shape Google: A Computer Vision Approach to Isometry Invariant Shape Retrieval." IEEE/CVF International Conference on Computer Vision Workshops, 2009. doi:10.1109/ICCVW.2009.5457682

Markdown

[Ovsjanikov et al. "Shape Google: A Computer Vision Approach to Isometry Invariant Shape Retrieval." IEEE/CVF International Conference on Computer Vision Workshops, 2009.](https://mlanthology.org/iccvw/2009/ovsjanikov2009iccvw-shape/) doi:10.1109/ICCVW.2009.5457682

BibTeX

@inproceedings{ovsjanikov2009iccvw-shape,
  title     = {{Shape Google: A Computer Vision Approach to Isometry Invariant Shape Retrieval}},
  author    = {Ovsjanikov, Maks and Bronstein, Alexander M. and Bronstein, Michael M. and Guibas, Leonidas J.},
  booktitle = {IEEE/CVF International Conference on Computer Vision Workshops},
  year      = {2009},
  pages     = {320-327},
  doi       = {10.1109/ICCVW.2009.5457682},
  url       = {https://mlanthology.org/iccvw/2009/ovsjanikov2009iccvw-shape/}
}