Building facade structure extraction method based on three-dimensional laser point cloud by considering semantic information
ABSTRACTBuilding facade structures serve as important data support for three-dimensional (3D) building modelling. A building facade structure extraction method based on 3D Laser Point Cloud Data (LPCD) by considering semantic information is proposed. The proposed method mainly involves three steps....
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2024-04-01
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| Series: | Annals of GIS |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/19475683.2024.2335953 |
| _version_ | 1797214294993010688 |
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| author | Xiaoyu Hu Yongzhi Wang Tao Zhou Deborah Simon Mwakapesa |
| author_facet | Xiaoyu Hu Yongzhi Wang Tao Zhou Deborah Simon Mwakapesa |
| author_sort | Xiaoyu Hu |
| collection | DOAJ |
| description | ABSTRACTBuilding facade structures serve as important data support for three-dimensional (3D) building modelling. A building facade structure extraction method based on 3D Laser Point Cloud Data (LPCD) by considering semantic information is proposed. The proposed method mainly involves three steps. First, an improved 3D LPCD semantic segmentation method is introduced to extract and label point clouds as the building structure and walls. Second, structure line segments are recognized from the initial building facade structure based on the Regulated Block RANSAC (RB-RANSAC) algorithm. Third, geometric information such as distance, vector and positional relationship between structure line segments is considered to optimize the initial building facade structure. The proposed method can effectively extract and fit segment structures by considering the semantic and geometric information, obtaining significantly accurate and concise building facade structures. Case studies on 3D LPCD of local buildings and open-source datasets (Semantic3D) prove the extraction accuracy and efficiency of the proposed method. |
| first_indexed | 2024-04-24T11:11:54Z |
| format | Article |
| id | doaj.art-806dbdbd5489479c82ace4692d47ea89 |
| institution | Directory Open Access Journal |
| issn | 1947-5683 1947-5691 |
| language | English |
| last_indexed | 2024-04-24T11:11:54Z |
| publishDate | 2024-04-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Annals of GIS |
| spelling | doaj.art-806dbdbd5489479c82ace4692d47ea892024-04-11T13:10:27ZengTaylor & Francis GroupAnnals of GIS1947-56831947-56912024-04-0111510.1080/19475683.2024.2335953Building facade structure extraction method based on three-dimensional laser point cloud by considering semantic informationXiaoyu Hu0Yongzhi Wang1Tao Zhou2Deborah Simon Mwakapesa3School of Geography Science and Geomatics Engineering, Suzhou University of Science and Technology, Suzhou, ChinaSchool of Geography Science and Geomatics Engineering, Suzhou University of Science and Technology, Suzhou, ChinaLanzhou Institute of Seismology, CEA, Lanzhou, Gansu, ChinaSchool of Civil and Surveying & Mapping Engineering, Jiangxi University of Science and Technology, Ganzhou, ChinaABSTRACTBuilding facade structures serve as important data support for three-dimensional (3D) building modelling. A building facade structure extraction method based on 3D Laser Point Cloud Data (LPCD) by considering semantic information is proposed. The proposed method mainly involves three steps. First, an improved 3D LPCD semantic segmentation method is introduced to extract and label point clouds as the building structure and walls. Second, structure line segments are recognized from the initial building facade structure based on the Regulated Block RANSAC (RB-RANSAC) algorithm. Third, geometric information such as distance, vector and positional relationship between structure line segments is considered to optimize the initial building facade structure. The proposed method can effectively extract and fit segment structures by considering the semantic and geometric information, obtaining significantly accurate and concise building facade structures. Case studies on 3D LPCD of local buildings and open-source datasets (Semantic3D) prove the extraction accuracy and efficiency of the proposed method.https://www.tandfonline.com/doi/10.1080/19475683.2024.2335953LiDAR databuilding facade structuresemantic segmentation |
| spellingShingle | Xiaoyu Hu Yongzhi Wang Tao Zhou Deborah Simon Mwakapesa Building facade structure extraction method based on three-dimensional laser point cloud by considering semantic information Annals of GIS LiDAR data building facade structure semantic segmentation |
| title | Building facade structure extraction method based on three-dimensional laser point cloud by considering semantic information |
| title_full | Building facade structure extraction method based on three-dimensional laser point cloud by considering semantic information |
| title_fullStr | Building facade structure extraction method based on three-dimensional laser point cloud by considering semantic information |
| title_full_unstemmed | Building facade structure extraction method based on three-dimensional laser point cloud by considering semantic information |
| title_short | Building facade structure extraction method based on three-dimensional laser point cloud by considering semantic information |
| title_sort | building facade structure extraction method based on three dimensional laser point cloud by considering semantic information |
| topic | LiDAR data building facade structure semantic segmentation |
| url | https://www.tandfonline.com/doi/10.1080/19475683.2024.2335953 |
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