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Article

A Graph-Based Approach for 3D Building Model Reconstruction from Airborne LiDAR Point Clouds

by 1,2, 1,2,*, 3, 1,2, 4, 4 and 1,2,*
1
Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China
2
School of Geographic Sciences, East China Normal University, Shanghai 200241, China
3
Department of Geography, Binghamton University, State University of New York, Binghamton, NY 13902, USA
4
Shanghai Surveying and Mapping Institute, 419 Wuning Rd., Shanghai 200063, China
*
Authors to whom correspondence should be addressed.
Academic Editors: Lei Wang, Xiaofeng Li and Prasad S. Thenkabail
Remote Sens. 2017, 9(1), 92; https://doi.org/10.3390/rs9010092
Received: 13 November 2016 / Revised: 15 December 2016 / Accepted: 12 January 2017 / Published: 20 January 2017
(This article belongs to the Special Issue Remote Sensing for 3D Urban Morphology)
3D building model reconstruction is of great importance for environmental and urban applications. Airborne light detection and ranging (LiDAR) is a very useful data source for acquiring detailed geometric and topological information of building objects. In this study, we employed a graph-based method based on hierarchical structure analysis of building contours derived from LiDAR data to reconstruct urban building models. The proposed approach first uses a graph theory-based localized contour tree method to represent the topological structure of buildings, then separates the buildings into different parts by analyzing their topological relationships, and finally reconstructs the building model by integrating all the individual models established through the bipartite graph matching process. Our approach provides a more complete topological and geometrical description of building contours than existing approaches. We evaluated the proposed method by applying it to the Lujiazui region in Shanghai, China, a complex and large urban scene with various types of buildings. The results revealed that complex buildings could be reconstructed successfully with a mean modeling error of 0.32 m. Our proposed method offers a promising solution for 3D building model reconstruction from airborne LiDAR point clouds. View Full-Text
Keywords: contour tree; bipartite graph matching; graph theory; building reconstruction; LiDAR contour tree; bipartite graph matching; graph theory; building reconstruction; LiDAR
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MDPI and ACS Style

Wu, B.; Yu, B.; Wu, Q.; Yao, S.; Zhao, F.; Mao, W.; Wu, J. A Graph-Based Approach for 3D Building Model Reconstruction from Airborne LiDAR Point Clouds. Remote Sens. 2017, 9, 92. https://doi.org/10.3390/rs9010092

AMA Style

Wu B, Yu B, Wu Q, Yao S, Zhao F, Mao W, Wu J. A Graph-Based Approach for 3D Building Model Reconstruction from Airborne LiDAR Point Clouds. Remote Sensing. 2017; 9(1):92. https://doi.org/10.3390/rs9010092

Chicago/Turabian Style

Wu, Bin, Bailang Yu, Qiusheng Wu, Shenjun Yao, Feng Zhao, Weiqing Mao, and Jianping Wu. 2017. "A Graph-Based Approach for 3D Building Model Reconstruction from Airborne LiDAR Point Clouds" Remote Sensing 9, no. 1: 92. https://doi.org/10.3390/rs9010092

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