Automatic Registration of Terrestrial and Airborne Point Clouds Using Building Outline Features

被引:36
作者
Cheng, Xiaolong [1 ,2 ]
Cheng, Xiaojun [2 ]
Li, Quan [2 ]
Ma, Liwei [3 ]
机构
[1] Jiangxi Univ Sci & Technol, Coll Architecture & Surveying & Mapping Engn, Ganzhou 341000, Peoples R China
[2] Tongji Univ, Coll Surveying & Geoinformat, Shanghai 200092, Peoples R China
[3] Parsons Brinckerhoff Inc, Transport Planning Dept, Shanghai 200092, Peoples R China
基金
中国国家自然科学基金;
关键词
Airborne laser scanning; building outline; global optimization method; registration; terrestrial laser scanning; LASER SCANNER; LIDAR DATA; EXTRACTION; MODELS;
D O I
10.1109/JSTARS.2017.2788054
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Terrestrial laser scanner (TLS) and airborne laser scanner (ALS) can effectively capture point clouds from side or top view, respectively. Registering point clouds captured by ALS and TLS provides an integrated data source for three-dimensional (3-D) reconstruction. However, registration is difficult between TLS and ALS data because of the differences in scanning perspectives, scanning area, and spatial resolutions. A new method that can achieve automatic horizontal registration with ALS and TLS data based on building contour features is proposed in this study. The key steps include horizontal and vertical registrations based on 2-D building outlines and ground planes in ALS and TLS data, respectively. First, the 2-D building outlines are extracted from both ALS and TLS data. Second, the horizontal registration is accomplished by using the four-point congruent sets method for initial registration and the global optimization method for refined registration. Finally, the ground surface in the same region of ALS and TLS data are fitted for vertical registration, and the average elevation difference between the corresponding ground planes is calculated as the translation parameter value in the vertical direction. The results indicate that the proposed method can successfully match ALS and TLS data with an accuracy of 0.2-m both in the horizontal and vertical directions.
引用
收藏
页码:628 / 638
页数:11
相关论文
共 27 条
  • [1] [Anonymous], 2011, INT ARCH PHOTOGRAMM
  • [2] How easy is matching 2D line models using local search?
    Beveridge, JR
    Riseman, EM
    [J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1997, 19 (06) : 564 - 579
  • [3] CLASSIFICATION OF AIRBORNE LASER SCANNING DATA USING GEOMETRIC MULTI-SCALE FEATURES AND DIFFERENT NEIGHBOURHOOD TYPES
    Blomley, R.
    Jutzi, B.
    Weinmann, M.
    [J]. XXIII ISPRS CONGRESS, COMMISSION III, 2016, 3 (03): : 169 - 176
  • [4] Automatic Extraction of Planar Clusters and their Contours on Building Facades Recorded by Terrestrial Laser Scanner
    Boulaassal, H.
    Landes, T.
    Grussenmeyer, P.
    [J]. INTERNATIONAL JOURNAL OF ARCHITECTURAL COMPUTING, 2009, 7 (01) : 1 - 20
  • [5] Coarse orientation of terrestrial laser scans in urban environments
    Brenner, C.
    Dold, C.
    Ripperda, N.
    [J]. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2008, 63 (01) : 4 - 18
  • [6] Semi-Automatic Registration of Airborne and Terrestrial Laser Scanning Data Using Building Corner Matching with Boundaries as Reliability Check
    Cheng, Liang
    Tong, Lihua
    Li, Manchun
    Liu, Yongxue
    [J]. REMOTE SENSING, 2013, 5 (12) : 6260 - 6283
  • [7] Building region derivation from LiDAR data using a reversed iterative mathematic morphological algorithm
    Cheng, Liang
    Zhao, Wei
    Han, Peng
    Zhang, Wen
    Shan, Jie
    Liu, Yongxue
    Li, Manchun
    [J]. OPTICS COMMUNICATIONS, 2013, 286 : 244 - 250
  • [8] [程效军 Cheng Xiaojun], 2015, [同济大学学报. 自然科学版, Journal of Tongji University. Natural Science], V43, P1419
  • [9] Cheng Xiaojun, 2012, Journal of Tongji University (Natural Science), V40, P1559, DOI 10.3969/j.issn.0253-374x.2012.10.022
  • [10] Line Matching Leveraged By Point Correspondences
    Fan, Bin
    Wu, Fuchao
    Hu, Zhanyi
    [J]. 2010 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2010, : 390 - 397