ML Anthology

Fast Recognition Using Adaptive Subdivisions of Transformation Space

Thomas M. Breuel
CVPR 1992 pp. 445-451
doi:10.1109/CVPR.1992.223152 /cvpr/1992/breuel1992cvpr-fast/

Abstract

An algorithm, RAST, for solving the bounded error recognition problem efficiently using adaptive subdivisions of transformation space, is presented. The RAST algorithm uses no heuristics and loses no solutions. It is a simple, efficient algorithm combining the ideas of multiresolution matching, Hough transform, search-based recognition, and bounded error recognition. Its performance is better than that of alignment and Hough transform methods, and, as opposed to these methods; RAST finds solutions satisfying simple, well-defined bounded error criteria.< <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

Breuel. "Fast Recognition Using Adaptive Subdivisions of Transformation Space." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1992. doi:10.1109/CVPR.1992.223152

Markdown

[Breuel. "Fast Recognition Using Adaptive Subdivisions of Transformation Space." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1992.](https://mlanthology.org/cvpr/1992/breuel1992cvpr-fast/) doi:10.1109/CVPR.1992.223152

BibTeX

@inproceedings{breuel1992cvpr-fast,
  title     = {{Fast Recognition Using Adaptive Subdivisions of Transformation Space}},
  author    = {Breuel, Thomas M.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1992},
  pages     = {445-451},
  doi       = {10.1109/CVPR.1992.223152},
  url       = {https://mlanthology.org/cvpr/1992/breuel1992cvpr-fast/}
}