ML Anthology

Approximation of Canonical Sets and Their Applications to 2D View Simplification

Trip Denton, Jeff Abrahamson, Ali Shokoufandeh
CVPR 2004 pp. 550-557
doi:10.1109/CVPR.2004.35 /cvpr/2004/denton2004cvpr-approximation/

Abstract

Given a set of patterns and a similarity measure between them, we would present an optimization framework to approximate a small subset, known as a canonical set, whose members closely resemble the members of the original set. We would present a combinatorial formulation of the canonical set problem in terms of quadratic optimization integer programming, present a relaxation through semidefinite programming, and propose a bounded performance rounding procedure for its approximation solution in polynomial time. Through a set of experiments we would investigate the application of canonical sets for computing a summary of views from a dense set of 2D views computed for a 3D object.

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Cite

Text

Denton et al. "Approximation of Canonical Sets and Their Applications to 2D View Simplification." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2004. doi:10.1109/CVPR.2004.35

Markdown

[Denton et al. "Approximation of Canonical Sets and Their Applications to 2D View Simplification." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2004.](https://mlanthology.org/cvpr/2004/denton2004cvpr-approximation/) doi:10.1109/CVPR.2004.35

BibTeX

@inproceedings{denton2004cvpr-approximation,
  title     = {{Approximation of Canonical Sets and Their Applications to 2D View Simplification}},
  author    = {Denton, Trip and Abrahamson, Jeff and Shokoufandeh, Ali},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2004},
  pages     = {550-557},
  doi       = {10.1109/CVPR.2004.35},
  url       = {https://mlanthology.org/cvpr/2004/denton2004cvpr-approximation/}
}