ML Anthology

Geometric Primitive Extraction Using a Genetic Algorithm

Gerhard Roth, Martin D. Levine
CVPR 1992 pp. 640-643
doi:10.1109/CVPR.1992.223120 /cvpr/1992/roth1992cvpr-geometric/

Abstract

A genetic algorithm based on a minimal subset representation of a geometric primitive is used to perform primitive extraction. A genetic algorithm is an optimization method that uses the metaphor of evolution, and a minimal subset is the smallest number of points necessary to define a unique instance of a geometric primitive. The approach is capable of extracting more complex primitives than the Hough transform. While similar to a hierarchical merging algorithm, it does not suffer from the problem of premature commitment.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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Cite

Text

Roth and Levine. "Geometric Primitive Extraction Using a Genetic Algorithm." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1992. doi:10.1109/CVPR.1992.223120

Markdown

[Roth and Levine. "Geometric Primitive Extraction Using a Genetic Algorithm." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1992.](https://mlanthology.org/cvpr/1992/roth1992cvpr-geometric/) doi:10.1109/CVPR.1992.223120

BibTeX

@inproceedings{roth1992cvpr-geometric,
  title     = {{Geometric Primitive Extraction Using a Genetic Algorithm}},
  author    = {Roth, Gerhard and Levine, Martin D.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1992},
  pages     = {640-643},
  doi       = {10.1109/CVPR.1992.223120},
  url       = {https://mlanthology.org/cvpr/1992/roth1992cvpr-geometric/}
}