Fast Alignment Using Probabilistic Indexing

CVPR 1993 pp. 387-392

doi:10.1109/CVPR.1993.341101 /cvpr/1993/olson1993cvpr-fast/

Abstract

The alignment method is a model-based object recognition technique that determines possible object transformations from three hypothesized matches of model and image points. For images and/or models with many features, the running time of the alignment method can be large. Methods of reducing the number of matches that must be examined are presented. The techniques described are the use of the probabilistic indexing system, and the elimination of groups of model points that produce large errors in the transformation determined by the alignment method. Results are presented which show that it is possible to achieve a speedup of over two orders of magnitude while still finding a correct alignment.<<ETX>>

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Cite

Text

Olson. "Fast Alignment Using Probabilistic Indexing." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1993. doi:10.1109/CVPR.1993.341101

Markdown

[Olson. "Fast Alignment Using Probabilistic Indexing." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1993.](https://mlanthology.org/cvpr/1993/olson1993cvpr-fast/) doi:10.1109/CVPR.1993.341101

BibTeX

@inproceedings{olson1993cvpr-fast,
  title     = {{Fast Alignment Using Probabilistic Indexing}},
  author    = {Olson, Clark F.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1993},
  pages     = {387-392},
  doi       = {10.1109/CVPR.1993.341101},
  url       = {https://mlanthology.org/cvpr/1993/olson1993cvpr-fast/}
}