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Accurate facade feature extraction method for buildings from three-dimensional point cloud data considering structural information
Wang, Yongzhi1; Ma, Yuqing1; Zhu, A-xing2,3,4,5,6; Zhao, Hui1; Liao, Lixia1
2018-05-01
Source PublicationISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
ISSN0924-2716
Volume139Pages:146-153
Corresponding AuthorZhu, A-xing(azhu@wisc.edu)
AbstractFacade features represent segmentations of building surfaces and can serve as a building framework. Extracting facade features from three-dimensional (3D) point cloud data (3D PCD) is an efficient method for 3D building modeling. By combining the advantages of 3D PCD and two-dimensional optical images, this study describes the creation of a highly accurate building facade feature extraction method from 3D PCD with a focus on structural information. The new extraction method involves three major steps: image feature extraction, exploration of the mapping method between the image features and 3D PCD, and optimization of the initial 3D PCD facade features considering structural information. Results show that the new method can extract the 3D PCD facade features of buildings more accurately and continuously. The new method is validated using a case study. In addition, the effectiveness of the new method is demonstrated by comparing it with the range image-extraction method and the optical image-extraction method in the absence of structural information. The 3D PCD facade features extracted by the new method can be applied in many fields, such as 3D building modeling and building information modeling. (C) 2017 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.
KeywordThree-dimensional point cloud data Two-dimensional optical images Structural information Facade features Three-dimensional building modeling
DOI10.1016/j.isprsjprs.2017.11.015
WOS KeywordFALSE DETECTION CONTROL ; LINE SEGMENT DETECTOR ; LIDAR DATA ; IMAGE
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[41601429] ; Natural Science Foundation of Jiangxi Provincial Department of Science and Technology[20171BAB203028]
Funding OrganizationNational Natural Science Foundation of China ; Natural Science Foundation of Jiangxi Provincial Department of Science and Technology
WOS Research AreaPhysical Geography ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS SubjectGeography, Physical ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS IDWOS:000431160100011
PublisherELSEVIER SCIENCE BV
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/55070
Collection中国科学院地理科学与资源研究所
Corresponding AuthorZhu, A-xing
Affiliation1.Jiangxi Univ Sci & Technol, Sch Architectural & Surveying & Mapping Engn, Ganzhou, Peoples R China
2.Nanjing Normal Univ, Key Lab Virtual Geog Environm, Nanjing, Jiangsu, Peoples R China
3.State Key Lab Cultivat Base Geog Environm Evolut, Nanjing, Jiangsu, Peoples R China
4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China
5.Univ Wisconsin, Dept Geog, Madison, WI 53706 USA
6.Jiangsu Ctr Collaborat Innovat Geog Informat Res, Nanjing, Jiangsu, Peoples R China
Recommended Citation
GB/T 7714
Wang, Yongzhi,Ma, Yuqing,Zhu, A-xing,et al. Accurate facade feature extraction method for buildings from three-dimensional point cloud data considering structural information[J]. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,2018,139:146-153.
APA Wang, Yongzhi,Ma, Yuqing,Zhu, A-xing,Zhao, Hui,&Liao, Lixia.(2018).Accurate facade feature extraction method for buildings from three-dimensional point cloud data considering structural information.ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,139,146-153.
MLA Wang, Yongzhi,et al."Accurate facade feature extraction method for buildings from three-dimensional point cloud data considering structural information".ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING 139(2018):146-153.
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