English

An Unsupervised, Iterative N-Dimensional Point-Set Registration Algorithm

Computer Vision and Pattern Recognition 2019-08-14 v1 Machine Learning

Abstract

An unsupervised, iterative point-set registration algorithm for an unlabeled (i.e. correspondence between points is unknown) N-dimensional Euclidean point-cloud is proposed. It is based on linear least squares, and considers all possible point pairings and iteratively aligns the two sets until the number of point pairs does not exceed the maximum number of allowable one-to-one pairings.

Keywords

Cite

@article{arxiv.1908.04384,
  title  = {An Unsupervised, Iterative N-Dimensional Point-Set Registration Algorithm},
  author = {A. Pasha Hosseinbor and R. Zhdanov and A. Ushveridze},
  journal= {arXiv preprint arXiv:1908.04384},
  year   = {2019}
}

Comments

arXiv admin note: text overlap with arXiv:1702.01870

R2 v1 2026-06-23T10:45:41.540Z