Acta Geodaetica et Cartographica Sinica >

2017 , Vol. 46 >Issue 9: 1123 - 1134

DOI: https://doi.org/10.11947/j.AGCS.2017.20160518

Accurate and Automatic Building Roof Extraction Using Neighborhood Information of Point Clouds

  • ZHAO Chuan ,
  • ZHANG Baoming ,
  • CHEN Xiaowei ,
  • GUO Haitao ,
  • LU Jun
Expand
  • 1. Institute of Surveying and Mapping, Information Engineering University, Zhengzhou 450001, China;
    2. State Key Laboratory of Geo-information Engineering, Xi'an 710054, China

Received date: 2016-10-25

  Revised date: 2017-08-09

  Online published: 2017-10-12

Supported by

The National Natural Science Foundation of China (No. 41601507);The Open Research Foundation of State Key Laboratory of Geo-information Engineering (No. SKLGIE2015-M-3-3)

Fold

Abstract

High accuracy building roof extraction from LiDAR data is the key to build topological relationship of building roofs and reconstruct buildings. Aiming at the poor adaptation and low extraction precision of existing roof extraction methods for complex building, an accurate and automatic building roof extraction method using neighborhood information of point clouds is proposed. Point clouds features are calculated by principle component analysis, and reliable seed points are selected after feature histogram construction. Initial roof surfaces are extracted quickly and precisely by the proposed local normal vector distribution density-based spatial clustering of applications with noise (LNVD-DBSCAN). Roof competition problem is solved effectively by the poll model based on neighborhood information. Experimental results show that the proposed method can extract building roofs automatically and precisely, and has preferable adaptation to buildings with different complexity, which is able to provide reliable roof information for building reconstruction.

Key words： building roofs; LiDAR data; neighborhood information; density-based clustering; point cloud; 3D building reconstruction

Cite this article

ZHAO Chuan , ZHANG Baoming , CHEN Xiaowei , GUO Haitao , LU Jun . Accurate and Automatic Building Roof Extraction Using Neighborhood Information of Point Clouds[J]. Acta Geodaetica et Cartographica Sinica, 2017 , 46(9) : 1123 -1134 . DOI: 10.11947/j.AGCS.2017.20160518

References

[1] 李怡静, 胡翔云, 张剑清, 等. 影像与LiDAR数据信息融合复杂场景下的道路自动提取[J]. 测绘学报, 2012, 41(6):870-876. LI Yijing, HU Xiangyun, ZHANG Jianying, et al. Automatic Road Extraction in Complex Scenes Based on Information Fusion from LiDAR Data and Remote Sensing Imagery[J]. Acta Geodaetica et Cartographica Sinica, 2012, 41(6):870-876.
[2] 徐文学, 杨必胜, 魏征, 等. 多标记点过程的LiDAR点云数据建筑物和树冠提取[J]. 测绘学报, 2013, 42(1):51-58. XU Wenxue, YANG Bisheng, WEI Zheng, et al. Building and Tree Crown Extraction from LiDAR Point Cloud Data Based on Multi-marked Point Process[J]. Acta Geodaetica et Cartographica Sinica, 2013, 42(1):51-58.
[3] 龚健雅, 崔婷婷, 单杰, 等. 利用车载移动测量数据的建筑物立面建模方法[J]. 武汉大学学报(信息科学版), 2015, 40(9):1137-1143. GONG Jianya, CUI Tingting, SHAN Jie, et al. A Survey on Facade Modeling Using LiDAR Point Clouds and Image Sequences Collected by Mobile Mapping Systems[J]. Geomatics and Information Science of Wuhan University, 2015, 40(9):1137-1143.
[4] 黄先锋, SOHN G, 王潇, 等. 基于带权点法向量的LiDAR数据屋顶检测方法[J]. 武汉大学学报(信息科学版), 2009, 34(1):24-27. HUANG Xianfeng, SOHN G, WANG Xiao, et al. Roof Detection Using LiDAR Data Based on Points' Normal with Weight[J]. Geomatics and Information Science of Wuhan University, 2009, 34(1):24-27.
[5] XU Bo, JIANG Wanshou, SHAN Jie, et al. Investigation on the Weighted RANSAC Approaches for Building Roof Plane Segmentation from LiDAR Point Clouds[J]. Remote Sensing, 2016, 8(1):5.
[6] YAN Jixing, SHAN Jie, JIANG Wanshou. A Global Optimization Approach to Roof Segmentation from Airborne LiDAR Point Clouds[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2014(94):183-193.
[7] WU Teng, HU Xiangyun, YE Lizhi. Fast and Accurate Plane Segmentation of Airborne LiDAR Point Cloud Using Cross-line Elements[J]. Remote Sensing, 2016, 8(5):383.
[8] SCHNABEL R, WAHL R, KLEIN R. Efficient RANSAC for Point-cloud Shape Detection[J]. Computer Graphics Forum, 2007, 26(2):214-226.
[9] TARSHA-KURDI F, LANDES T, GRUSSENMEYER P. Hough-transform and Extended RANSAC Algorithms for Automatic Detection of 3D Building Roof Planes from LiDAR Data[C]//International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences. Strasbourg:ISPRS, 2007:407-412.
[10] VOSSELMAN G, DIJKMAN S. 3D Building Model Reconstruction from Point Clouds and Ground Plans[C]//International Archives of Photogrammetry and Remote Sensing. Annapolis, MD, USA:ISPRS, 2001:37-43.
[11] RABBANI T, VAN DEN HEUVEL F A, VOSSELMAN G. Segmentation of Point Clouds Using Smoothness Constraint[C]//International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences. Delft:ISPRS, 2006:248-253.
[12] 庞世燕, 刘亚文, 左志奇, 等. 结合区域增长法和TIN边缘分割的建筑物立面几何特征提取[J]. 武汉大学学报(信息科学版), 2015, 40(1):102-106. PANG Shiyan, LIU Yawen, ZUO Zhiqi, et al. Combination of Region Growing and TIN Edge Segmentation for Extraction of Geometric Features on Building Facades[J]. Geomatics and Information Science of Wuhan University, 2015, 40(1):102-106.
[13] VOSSELMAN G. Automated Planimetric Quality Control in High Accuracy Airborne Laser Scanning Surveys[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2012(74):90-100.
[14] 高广, 马洪超, 张良. 利用合成算法从LiDAR数据提取屋顶面[J]. 武汉大学学报(信息科学版), 2014, 39(10):1225-1230. GAO Guang, MA Hongchao, ZHANG Liang. Automatic Extraction of Building Roofs from LiDAR Data Using a Hybridized Method[J]. Geomatics and Information Science of Wuhan University, 2014, 39(10):1225-1230.
[15] SAMPATH A, SHAN Jie. Segmentation and Reconstruction of Polyhedral Building Roofs from Aerial LiDAR Point Clouds[J]. IEEE Transactions on Geoscience and Remote Sensing, 2010, 48(3):1554-1567.
[16] FERRAZ A, BRETAR F, JACQUEMOUD S, et al. 3D Segmentation of Forest Structure Using a Mean-shift Based Algorithm[C]//Proceedings of the 17th IEEE International Conference on Image Processing. Hong Kong, China:IEEE, 2010:1413-1416.
[17] LIU Xiuping, ZHANG Jie, CAO Junjie, et al. Quality Point Cloud Normal Estimation by Guided Least Squares Representation[J]. Computers & Graphics, 2015(51):106-116.
[18] PAULY M. Point Primitives for Interactive Modeling and Processing of 3D Geometry[D]. Zurich:ETH Zurich, 2003.
[19] 胡伟. 机载LiDAR数据三维建筑物模型重建方法研究[D]. 焦作:河南理工大学, 2012. HU Wei. Research on 3D Building Reconstruction from Airborne LiDAR Data[D]. Jiaozuo:Henan Polytechnic University, 2012.
[20] 孙吉贵, 刘杰, 赵连宇. 聚类算法研究[J]. 软件学报, 2008, 19(1):48-61. SUN Jigui, LIU Jie, ZHAO Lianyu. Clustering Algorithms Research[J]. Journal of Software, 2008, 19(1):48-61.
[21] BIRANT D, KUT A. ST-DBSCAN:An Algorithm for Clustering Spatial-temporal Data[J]. Data & Knowledge Engineering, 2007, 60(1):208-221.
[22] BORDOGNA G, IENCO D. Fuzzy Core DBSCAN Clustering Algorithm[C]//LAURENT A, STRAUSS O, BOUCHON-MEUNIER B, et al. Information Processing and Management of Uncertainty in Knowledge-based Systems. Cham:Springer International Publishing, 2014:100-109.
[23] YAN W Y, MORSY S, SHAKER A, et al. Automatic Extraction of Highway Light Poles and Towers from Mobile LiDAR Data[J]. Optics & Laser Technology, 2016, 77:162-168.
[24] 吕峰. 利用航空影像和LiDAR点云进行建筑物重建的方法研究[D]. 成都:西南交通大学, 2013. LV Feng. Building Reconstruction Methods Study Based on Aerial Image and LiDAR Point Cloud[D]. Chengdu:Southwest Jiaotong University, 2013.
[25] AWRANGJEB M, FRASER C S. An Automatic and Threshold-free Performance Evaluation System for Building Extraction Techniques from Airborne LiDAR Data[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014, 7(10):4184-4198.
[26] ISPRS. ISPRS Test Project on Urban Classification and 3D Building Reconstruction[DB/OL]. (2016-08-13)[2016-09-28]. http://www2.isprs.org/commissions/comm3/wg4/detection-and-reconstruction.html.
[27] OpenTopography. NCALM Project. PI:Shane Grigsby, University of Colorado, Boulder[DB/OL]. (2016-09-10)[2016-12-10]. https://doi.org/10.5069/G9ZC80SR.
[28] FISCHLER M A, BOLLES, R C. Random Sample Consensus:A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography[J]. Communications of the ACM, 1981, 24(6):381-395.
[29] TORR P H S, ZISSERMAN A. MLESAC:A New Robust Estimator with Application to Estimating Image Geometry[J]. Computer Vision and Image Understanding, 2000, 78(1):138-156.
Options
Outlines

/

〈 〉