An unsupervised, iterative $N$-dimensional point-set  registration algorithm

P. Hosseinbor; R. Zhdanov; A. Ushveridze

doi:10.37863/umzh.v74i3.6969

P. Hosseinbor BIO-key International, Eagan, MN, USA
R. Zhdanov CyberOptics, Minneapolis, MN, USA
A. Ushveridze Algostream, Plymouth, MN, USA

DOI: https://doi.org/10.37863/umzh.v74i3.6969

Keywords: Unsupervised method, point-registration algorithm, least square optimization

Abstract

UDC 517.9

An unsupervised, iterative $N$-dimensional point-set registration algorithm for unlabeled data (i.e., correspondence between points is unknown) and based on linear least squares is proposed. The algorithm 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.

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