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2PNS++ point-cloud registration via hash of invariants and local compatibility check

In this research, we use hash match of invariants under fixed pair length and local compatibility check of positions or normal vectors to improve the efficiency of two-point normal set (2PNS) point cloud registration algorithm. On the one hand, we use the key value formed by the invariants of base p...

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Detalles Bibliográficos
Autores principales: Liu, Hai, Wang, Shulin, Zhao, Donghong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10653450/
https://www.ncbi.nlm.nih.gov/pubmed/37972048
http://dx.doi.org/10.1371/journal.pone.0287134
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author Liu, Hai
Wang, Shulin
Zhao, Donghong
author_facet Liu, Hai
Wang, Shulin
Zhao, Donghong
author_sort Liu, Hai
collection PubMed
description In this research, we use hash match of invariants under fixed pair length and local compatibility check of positions or normal vectors to improve the efficiency of two-point normal set (2PNS) point cloud registration algorithm. On the one hand, we use the key value formed by the invariants of base point pairs of fixed length to construct and retrieve the hash table to realize the matching of base point pairs in the two point clouds to be registered to speed up the extraction of candidate transformation matrices. On the other hand, the time consumed in the verification phase is reduced by checking the compatibility between the positions or normal vectors of the corresponding points in the specific areas of the two point clouds under the transformation from the candidate matrix. Through these two improvements, the algorithm significantly reduces the time spent in the point cloud registration algorithm.
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spelling pubmed-106534502023-11-16 2PNS++ point-cloud registration via hash of invariants and local compatibility check Liu, Hai Wang, Shulin Zhao, Donghong PLoS One Research Article In this research, we use hash match of invariants under fixed pair length and local compatibility check of positions or normal vectors to improve the efficiency of two-point normal set (2PNS) point cloud registration algorithm. On the one hand, we use the key value formed by the invariants of base point pairs of fixed length to construct and retrieve the hash table to realize the matching of base point pairs in the two point clouds to be registered to speed up the extraction of candidate transformation matrices. On the other hand, the time consumed in the verification phase is reduced by checking the compatibility between the positions or normal vectors of the corresponding points in the specific areas of the two point clouds under the transformation from the candidate matrix. Through these two improvements, the algorithm significantly reduces the time spent in the point cloud registration algorithm. Public Library of Science 2023-11-16 /pmc/articles/PMC10653450/ /pubmed/37972048 http://dx.doi.org/10.1371/journal.pone.0287134 Text en © 2023 Liu et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Liu, Hai
Wang, Shulin
Zhao, Donghong
2PNS++ point-cloud registration via hash of invariants and local compatibility check
title 2PNS++ point-cloud registration via hash of invariants and local compatibility check
title_full 2PNS++ point-cloud registration via hash of invariants and local compatibility check
title_fullStr 2PNS++ point-cloud registration via hash of invariants and local compatibility check
title_full_unstemmed 2PNS++ point-cloud registration via hash of invariants and local compatibility check
title_short 2PNS++ point-cloud registration via hash of invariants and local compatibility check
title_sort 2pns++ point-cloud registration via hash of invariants and local compatibility check
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10653450/
https://www.ncbi.nlm.nih.gov/pubmed/37972048
http://dx.doi.org/10.1371/journal.pone.0287134
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