PMO OpenIR
A Novel Framework for 2.5-D Building Contouring From Large-Scale Residential Scenes
Du, Jianli1,2; Chen, Dong3,4; Wang, Ruisheng4; Peethambaran, Jiju5; Mathiopoulos, P. Takis6; Xie, Lei4; Yun, Ting7
2019-06-01
Source PublicationIEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
ISSN0196-2892
Volume57Issue:6Pages:4121-4145
Corresponding AuthorChen, Dong(chendong@njfu.edu.cn) ; Wang, Ruisheng(ruiswang@ucalgary.ca)
AbstractThis paper introduces a novel methodology for residential building contouring from large-scale airborne point clouds. Unlike other methods that handle linearization and regularization of the linear primitives separately by imposing rigid constraints, we propose an optimization-based linearization and global regularization to form accurate, topologically error-free, and lightweight polygons. To this end, we enhance the classic density-based spatial clustering of applications with noise algorithm to segment individual building entities at the instance level. The initial contours of each individual building are then delineated and further decomposed by a novel topologically aware propagation process and a global optimization technique. The decomposed linear primitives are fed into the global regularization step, from which the regular shapes are learned and enforced hierarchically by imposing constraints, such as parallelism, homogeneity, orthogonality, and collinearity. Based on the concept of hybrid representation, the regularized and unaltered linear primitives are jointly connected in an esthetic way. Various experiments using representative buildings and large-scale residential scenes from the Dutch AHN3 data set have shown that the proposed methodology generates meaningful building contouring representation in terms of accuracy, compactness, topology, and levels of detail abstraction while being robust and scalable.
Keywordairborne laser scanning (ALS) building abstraction building contour decomposition building contours building regularization large-scale airborne point clouds LoD1 building models
DOI10.1109/TGRS.2019.2901539
WOS KeywordAUTOMATIC CONSTRUCTION ; RECONSTRUCTION ; MODEL ; REGULARIZATION ; ALGORITHMS ; EXTRACTION ; FOOTPRINTS ; IMAGES
Indexed BySCI
Language英语
WOS Research AreaGeochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
WOS SubjectGeochemistry & Geophysics ; Engineering, Electrical & Electronic ; Remote Sensing ; Imaging Science & Photographic Technology
WOS IDWOS:000470019800079
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://libir.pmo.ac.cn/handle/332002/26998
Collection中国科学院紫金山天文台
Corresponding AuthorChen, Dong; Wang, Ruisheng
Affiliation1.Wuhan Univ, Sch Geodesy & Geomat, Wuhan 430079, Hubei, Peoples R China
2.Chinese Acad Sci, Purple Mt Observ, Nanjing 210034, Jiangsu, Peoples R China
3.Nanjing Forestry Univ, Coll Civil Engn, Nanjing 210037, Jiangsu, Peoples R China
4.Univ Calgary, Dept Geomat Engn, Calgary, AB T2N 1N4, Canada
5.St Marys Univ, Dept Math & Comp Sci, Halifax, NS B3P 2M6, Canada
6.Univ Athens, Dept Informat & Telecommun, Athens 15784, Greece
7.Nanjing Forestry Univ, Coll Informat Sci & Technol, Nanjing 210037, Jiangsu, Peoples R China
Recommended Citation
GB/T 7714
Du, Jianli,Chen, Dong,Wang, Ruisheng,et al. A Novel Framework for 2.5-D Building Contouring From Large-Scale Residential Scenes[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2019,57(6):4121-4145.
APA Du, Jianli.,Chen, Dong.,Wang, Ruisheng.,Peethambaran, Jiju.,Mathiopoulos, P. Takis.,...&Yun, Ting.(2019).A Novel Framework for 2.5-D Building Contouring From Large-Scale Residential Scenes.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,57(6),4121-4145.
MLA Du, Jianli,et al."A Novel Framework for 2.5-D Building Contouring From Large-Scale Residential Scenes".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 57.6(2019):4121-4145.
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