Automated registration of dense terrestrial laser-scanning point clouds using curves

被引:93
|
作者
Yang, Bisheng [1 ]
Zang, Yufu [1 ]
机构
[1] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Peoples R China
基金
美国国家科学基金会;
关键词
Shape similarity; Curve matching; Point cloud registration; Deformation energy model; Terrestrial laser scanning; Feature extraction; ALGORITHM; SURFACE; SCANS;
D O I
10.1016/j.isprsjprs.2014.05.012
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
This paper proposes an automatic method for registering terrestrial laser scans in terms of robustness and accuracy. The proposed method uses spatial curves as matching primitives to overcome the limitations of registration methods based on points, lines, or patches as primitives. These methods often have difficulty finding correspondences between the scanned point clouds of freeform surfaces (e.g., statues, cultural heritage). The proposed method first clusters visually prominent points selected according to their associated geometric curvatures to extract crest lines which describe the shape characteristics of point clouds. Second, a deformation energy model is proposed to measure the shape similarity of these crest lines to select the correct matching-curve pairs. Based on these pairs, good initial orientation parameters can be obtained, resulting in fine registration. Experiments were undertaken to evaluate the robustness and accuracy of the proposed method, demonstrating a reliable and stable solution for accurately registering complex scenes without good initial alignment. (C) 2014 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:109 / 121
页数:13
相关论文
共 50 条
  • [1] Automatic Registration of Terrestrial Laser Scanning Point Clouds using Panoramic Reflectance Images
    Kang, Zhizhong
    Li, Jonathan
    Zhang, Liqiang
    Zhao, Qile
    Zlatanova, Sisi
    [J]. SENSORS, 2009, 9 (04) : 2621 - 2646
  • [2] AUTOMATIC REGISTRATION OF TREE POINT CLOUDS FROM TERRESTRIAL LASER SCANNING
    Zhou, Guiyun
    Cao, Shuai
    Sun, Zhongxuan
    [J]. 2015 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2015, : 561 - 564
  • [3] Assessing log geometry and wood quality in standing timber using terrestrial laser-scanning point clouds
    Pyorala, Jiri
    Kankare, Ville
    Liang, Xinlian
    Saarinen, Ninni
    Rikala, Juha
    Kivinen, Veli-Pekka
    Sipi, Marketta
    Holopainen, Markus
    Hyyppa, Juha
    Vastaranta, Mikko
    [J]. FORESTRY, 2019, 92 (02): : 177 - 187
  • [4] An automated method to register airborne and terrestrial laser scanning point clouds
    Yang, Bisheng
    Zang, Yufu
    Dong, Zhen
    Huang, Ronggang
    [J]. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2015, 109 : 62 - 76
  • [5] Entropy-Based Registration of Point Clouds Using Terrestrial Laser Scanning and Smartphone GPS
    Chen, Maolin
    Wang, Siying
    Wang, Mingwei
    Wan, Youchuan
    He, Peipei
    [J]. SENSORS, 2017, 17 (01)
  • [6] Structural assessment using terrestrial laser scanning point clouds
    Truong-Hong, Linh
    Lindenbergh, Roderik
    Nguyen, Thu Anh
    [J]. INTERNATIONAL JOURNAL OF BUILDING PATHOLOGY AND ADAPTATION, 2022, 40 (03) : 345 - 379
  • [7] Registration of oblique photography point clouds with terrestrial laser scanning point clouds based on geometric features of irregular building
    Xu, Jinghai
    Jing, Haoran
    Shen, Nan
    [J]. SURVEY REVIEW, 2024, 56 (398) : 509 - 524
  • [8] Registration of Laser Scanning Point Clouds: A Review
    Cheng, Liang
    Chen, Song
    Liu, Xiaoqiang
    Xu, Hao
    Wu, Yang
    Li, Manchun
    Chen, Yanming
    [J]. SENSORS, 2018, 18 (05)
  • [9] Registration of Long-Strip Terrestrial Laser Scanning Point Clouds Using RANSAC and Closed Constraint Adjustment
    Zheng, Li
    Yu, Manzhu
    Song, Mengxiao
    Stefanidis, Anthony
    Ji, Zheng
    Yang, Chaowei
    [J]. REMOTE SENSING, 2016, 8 (04):
  • [10] Automated Segmentation of Leaves From Deciduous Trees in Terrestrial Laser Scanning Point Clouds
    Koma, Zs
    Rutzinger, M.
    Bremer, M.
    [J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2018, 15 (09) : 1456 - 1460