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Voxel segmentation-based 3D building detection algorithm for airborne LIDAR data
Among traditional Light Detection And Ranging (LIDAR) data representations such as raster grid, triangulated irregular network, point clouds and octree, the explicit 3D nature of voxel-based representation makes it a promising alternative. Despite the benefit of voxel-based representation, voxel-bas...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6310284/ https://www.ncbi.nlm.nih.gov/pubmed/30592729 http://dx.doi.org/10.1371/journal.pone.0208996 |
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author | Wang, Liying Xu, Yan Li, Yu Zhao, Yuanding |
author_facet | Wang, Liying Xu, Yan Li, Yu Zhao, Yuanding |
author_sort | Wang, Liying |
collection | PubMed |
description | Among traditional Light Detection And Ranging (LIDAR) data representations such as raster grid, triangulated irregular network, point clouds and octree, the explicit 3D nature of voxel-based representation makes it a promising alternative. Despite the benefit of voxel-based representation, voxel-based algorithms have rarely been used for building detection. In this paper, a voxel segmentation-based 3D building detection algorithm is developed for separating building and nonbuilding voxels. The proposed algorithm first voxelizes the LIDAR point cloud into a grayscale voxel structure in which the grayscale of the voxel corresponds to the quantized mean intensity of the LIDAR points within the voxel. The voxelized dataset is segmented into multiple 3D-connected regions depending on the connectivity and grayscale similarity among voxels. The 3D-connected regions corresponding to the building roof and facade are detected sequentially according to characteristics such as their area, density, elevation difference and location. The obtained results for the detected buildings are evaluated by the LIDAR data provided by working group III/4 of ISPRS, which demonstrate a high rate of success. Average completeness, correctness, quality, and kappa coefficient indexes values of 90.0%, 96.0%, 88.1% and 88.7%, respectively, are obtained for buildings. |
format | Online Article Text |
id | pubmed-6310284 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-63102842019-01-08 Voxel segmentation-based 3D building detection algorithm for airborne LIDAR data Wang, Liying Xu, Yan Li, Yu Zhao, Yuanding PLoS One Research Article Among traditional Light Detection And Ranging (LIDAR) data representations such as raster grid, triangulated irregular network, point clouds and octree, the explicit 3D nature of voxel-based representation makes it a promising alternative. Despite the benefit of voxel-based representation, voxel-based algorithms have rarely been used for building detection. In this paper, a voxel segmentation-based 3D building detection algorithm is developed for separating building and nonbuilding voxels. The proposed algorithm first voxelizes the LIDAR point cloud into a grayscale voxel structure in which the grayscale of the voxel corresponds to the quantized mean intensity of the LIDAR points within the voxel. The voxelized dataset is segmented into multiple 3D-connected regions depending on the connectivity and grayscale similarity among voxels. The 3D-connected regions corresponding to the building roof and facade are detected sequentially according to characteristics such as their area, density, elevation difference and location. The obtained results for the detected buildings are evaluated by the LIDAR data provided by working group III/4 of ISPRS, which demonstrate a high rate of success. Average completeness, correctness, quality, and kappa coefficient indexes values of 90.0%, 96.0%, 88.1% and 88.7%, respectively, are obtained for buildings. Public Library of Science 2018-12-28 /pmc/articles/PMC6310284/ /pubmed/30592729 http://dx.doi.org/10.1371/journal.pone.0208996 Text en © 2018 Wang et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://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 Wang, Liying Xu, Yan Li, Yu Zhao, Yuanding Voxel segmentation-based 3D building detection algorithm for airborne LIDAR data |
title | Voxel segmentation-based 3D building detection algorithm for airborne LIDAR data |
title_full | Voxel segmentation-based 3D building detection algorithm for airborne LIDAR data |
title_fullStr | Voxel segmentation-based 3D building detection algorithm for airborne LIDAR data |
title_full_unstemmed | Voxel segmentation-based 3D building detection algorithm for airborne LIDAR data |
title_short | Voxel segmentation-based 3D building detection algorithm for airborne LIDAR data |
title_sort | voxel segmentation-based 3d building detection algorithm for airborne lidar data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6310284/ https://www.ncbi.nlm.nih.gov/pubmed/30592729 http://dx.doi.org/10.1371/journal.pone.0208996 |
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