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

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

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 n...

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Hauptverfasser: Hosseinbor, A. Pasha, Zhdanov, R, Ushveridze, A
Format: Artikel
Sprache:eng
Schlagworte:
Computer Science - Computer Vision and Pattern Recognition
Computer Science - Learning
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Beschreibung
Zusammenfassung: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.
DOI:10.48550/arxiv.1908.04384