Evaluation of the Convergence Region of an Automated Registration Method for 3D Laser Scanner Point Clouds

Using three dimensional point clouds from both simulated and real datasets from close and terrestrial laser scanners, the rotational and translational convergence regions of Geometric Primitive Iterative Closest Points (GP-ICP) are empirically evaluated. The results demonstrate the GP-ICP has a larg...

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Detalles Bibliográficos
Autor principal: Bae, Kwang-Ho
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2009
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3280749/
https://www.ncbi.nlm.nih.gov/pubmed/22389603
http://dx.doi.org/10.3390/s90100355
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author Bae, Kwang-Ho
author_facet Bae, Kwang-Ho
author_sort Bae, Kwang-Ho
collection PubMed
description Using three dimensional point clouds from both simulated and real datasets from close and terrestrial laser scanners, the rotational and translational convergence regions of Geometric Primitive Iterative Closest Points (GP-ICP) are empirically evaluated. The results demonstrate the GP-ICP has a larger rotational convergence region than the existing methods, e.g., the Iterative Closest Point (ICP).
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spelling pubmed-32807492012-03-02 Evaluation of the Convergence Region of an Automated Registration Method for 3D Laser Scanner Point Clouds Bae, Kwang-Ho Sensors (Basel) Article Using three dimensional point clouds from both simulated and real datasets from close and terrestrial laser scanners, the rotational and translational convergence regions of Geometric Primitive Iterative Closest Points (GP-ICP) are empirically evaluated. The results demonstrate the GP-ICP has a larger rotational convergence region than the existing methods, e.g., the Iterative Closest Point (ICP). Molecular Diversity Preservation International (MDPI) 2009-01-08 /pmc/articles/PMC3280749/ /pubmed/22389603 http://dx.doi.org/10.3390/s90100355 Text en © 2009 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Bae, Kwang-Ho
Evaluation of the Convergence Region of an Automated Registration Method for 3D Laser Scanner Point Clouds
title Evaluation of the Convergence Region of an Automated Registration Method for 3D Laser Scanner Point Clouds
title_full Evaluation of the Convergence Region of an Automated Registration Method for 3D Laser Scanner Point Clouds
title_fullStr Evaluation of the Convergence Region of an Automated Registration Method for 3D Laser Scanner Point Clouds
title_full_unstemmed Evaluation of the Convergence Region of an Automated Registration Method for 3D Laser Scanner Point Clouds
title_short Evaluation of the Convergence Region of an Automated Registration Method for 3D Laser Scanner Point Clouds
title_sort evaluation of the convergence region of an automated registration method for 3d laser scanner point clouds
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3280749/
https://www.ncbi.nlm.nih.gov/pubmed/22389603
http://dx.doi.org/10.3390/s90100355
work_keys_str_mv AT baekwangho evaluationoftheconvergenceregionofanautomatedregistrationmethodfor3dlaserscannerpointclouds

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