ML Anthology

Convex Shape Decomposition

Hairong Liu, Wenyu Liu, Longin Jan Latecki
CVPR 2010 pp. 97-104
doi:10.1109/CVPR.2010.5540225 /cvpr/2010/liu2010cvpr-convex/

Abstract

In this paper, we propose a new shape decomposition method, called convex shape decomposition. We formalize the convex decomposition problem as an integer linear programming problem, and obtain approximate optimal solution by minimizing the total cost of decomposition under some concavity constraints. Our method is based on Morse theory and combines information from multiple Morse functions. The obtained decomposition provides a compact representation, both geometrical and topological, of original object. Our experiments show that such representation is very useful in many applications.

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Cite

Text

Liu et al. "Convex Shape Decomposition." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2010. doi:10.1109/CVPR.2010.5540225

Markdown

[Liu et al. "Convex Shape Decomposition." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2010.](https://mlanthology.org/cvpr/2010/liu2010cvpr-convex/) doi:10.1109/CVPR.2010.5540225

BibTeX

@inproceedings{liu2010cvpr-convex,
  title     = {{Convex Shape Decomposition}},
  author    = {Liu, Hairong and Liu, Wenyu and Latecki, Longin Jan},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2010},
  pages     = {97-104},
  doi       = {10.1109/CVPR.2010.5540225},
  url       = {https://mlanthology.org/cvpr/2010/liu2010cvpr-convex/}
}