ML Anthology

A New Algorithm for Non-Rigid Point Matching

Haili Chui, Anand Rangarajan
CVPR 2000 pp. 2044-2051
doi:10.1109/CVPR.2000.854733 /cvpr/2000/chui2000cvpr-new/

Abstract

We present a new robust point matching algorithm (RPM) that can jointly estimate the correspondence and non-rigid transformations between two point-sets that may be of different sizes. The algorithm utilizes the soft assign for the correspondence and the thin-plate spline for the non-rigid mapping. Embedded within a deterministic annealing framework, the algorithm can automatically reject a fraction of the points as outliers. Experiments on both 2D synthetic point-sets with varying degrees of deformation, noise and outliers, and on real 3D sulcal point-sets (extracted from brain MRI) demonstrate the robustness of the algorithm.

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Cite

Text

Chui and Rangarajan. "A New Algorithm for Non-Rigid Point Matching." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2000. doi:10.1109/CVPR.2000.854733

Markdown

[Chui and Rangarajan. "A New Algorithm for Non-Rigid Point Matching." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2000.](https://mlanthology.org/cvpr/2000/chui2000cvpr-new/) doi:10.1109/CVPR.2000.854733

BibTeX

@inproceedings{chui2000cvpr-new,
  title     = {{A New Algorithm for Non-Rigid Point Matching}},
  author    = {Chui, Haili and Rangarajan, Anand},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2000},
  pages     = {2044-2051},
  doi       = {10.1109/CVPR.2000.854733},
  url       = {https://mlanthology.org/cvpr/2000/chui2000cvpr-new/}
}