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Robust Mesh Segmentation Using Feature-Aware Region Fusion †

This paper introduces a simple but powerful segmentation algorithm for 3D meshes. Our algorithm consists of two stages: over-segmentation and region fusion. In the first stage, adaptive space partition is applied to perform over-segmentation, which is very efficient. In the second stage, we define a...

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Detalles Bibliográficos
Autores principales: Wu, Lulu, Hou, Yu, Xu, Junli, Zhao, Yong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9824490/
https://www.ncbi.nlm.nih.gov/pubmed/36617011
http://dx.doi.org/10.3390/s23010416
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author Wu, Lulu
Hou, Yu
Xu, Junli
Zhao, Yong
author_facet Wu, Lulu
Hou, Yu
Xu, Junli
Zhao, Yong
author_sort Wu, Lulu
collection PubMed
description This paper introduces a simple but powerful segmentation algorithm for 3D meshes. Our algorithm consists of two stages: over-segmentation and region fusion. In the first stage, adaptive space partition is applied to perform over-segmentation, which is very efficient. In the second stage, we define a new intra-region difference, inter-region difference, and fusion condition with the help of various shape features and propose an iterative region fusion method. As the region fusion process is feature aware, our algorithm can deal with complex 3D meshes robustly. Massive qualitative and quantitative experiments also validate the advantages of the proposed algorithm.
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spelling pubmed-98244902023-01-08 Robust Mesh Segmentation Using Feature-Aware Region Fusion † Wu, Lulu Hou, Yu Xu, Junli Zhao, Yong Sensors (Basel) Article This paper introduces a simple but powerful segmentation algorithm for 3D meshes. Our algorithm consists of two stages: over-segmentation and region fusion. In the first stage, adaptive space partition is applied to perform over-segmentation, which is very efficient. In the second stage, we define a new intra-region difference, inter-region difference, and fusion condition with the help of various shape features and propose an iterative region fusion method. As the region fusion process is feature aware, our algorithm can deal with complex 3D meshes robustly. Massive qualitative and quantitative experiments also validate the advantages of the proposed algorithm. MDPI 2022-12-30 /pmc/articles/PMC9824490/ /pubmed/36617011 http://dx.doi.org/10.3390/s23010416 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Wu, Lulu
Hou, Yu
Xu, Junli
Zhao, Yong
Robust Mesh Segmentation Using Feature-Aware Region Fusion †
title Robust Mesh Segmentation Using Feature-Aware Region Fusion †
title_full Robust Mesh Segmentation Using Feature-Aware Region Fusion †
title_fullStr Robust Mesh Segmentation Using Feature-Aware Region Fusion †
title_full_unstemmed Robust Mesh Segmentation Using Feature-Aware Region Fusion †
title_short Robust Mesh Segmentation Using Feature-Aware Region Fusion †
title_sort robust mesh segmentation using feature-aware region fusion †
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9824490/
https://www.ncbi.nlm.nih.gov/pubmed/36617011
http://dx.doi.org/10.3390/s23010416
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AT houyu robustmeshsegmentationusingfeatureawareregionfusion
AT xujunli robustmeshsegmentationusingfeatureawareregionfusion
AT zhaoyong robustmeshsegmentationusingfeatureawareregionfusion