An unsupervised, iterative $N$-dimensional point-set registration algorithm
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 n...
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| Datum: | 2022 |
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| Hauptverfasser: | , , |
| Format: | Artikel |
| Sprache: | Englisch |
| Veröffentlicht: |
Institute of Mathematics, NAS of Ukraine
2022
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| Online Zugang: | https://umj.imath.kiev.ua/index.php/umj/article/view/6969 |
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| Назва журналу: | Ukrains’kyi Matematychnyi Zhurnal |
| Завантажити файл: |  |
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Ukrains’kyi Matematychnyi Zhurnal| Zusammenfassung: | 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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| DOI: | 10.37863/umzh.v74i3.6969 |