ML Anthology

Non-Iterative Contextual Correspondence Matching

William J. Christmas, Josef Kittler, Maria Petrou
ECCV 1994 pp. 137-142
doi:10.1007/BFB0028343 /eccv/1994/christmas1994eccv-non/

Abstract

In this paper, we develop a framework for the non-iterative matching of symbolic structures using contextual information. It is based on Bayesian reasoning and involves the explicit modelling of the binary relations between the objects. The difference between this and previously developed theories of the kind lies in the assumption that the binary relations used are derivable from the unary measurements that refer to individual objects. This leads to a non-iterative formula for probabilistic reasoning which is amenable to real-time implementation and produces good results. The theory is demonstrated using an application of automatic map registration.

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Cite

Text

Christmas et al. "Non-Iterative Contextual Correspondence Matching." European Conference on Computer Vision, 1994. doi:10.1007/BFB0028343

Markdown

[Christmas et al. "Non-Iterative Contextual Correspondence Matching." European Conference on Computer Vision, 1994.](https://mlanthology.org/eccv/1994/christmas1994eccv-non/) doi:10.1007/BFB0028343

BibTeX

@inproceedings{christmas1994eccv-non,
  title     = {{Non-Iterative Contextual Correspondence Matching}},
  author    = {Christmas, William J. and Kittler, Josef and Petrou, Maria},
  booktitle = {European Conference on Computer Vision},
  year      = {1994},
  pages     = {137-142},
  doi       = {10.1007/BFB0028343},
  url       = {https://mlanthology.org/eccv/1994/christmas1994eccv-non/}
}