Journals Articles Conferences News About CLP
Submit a paper Email Alert
Search
Search
Articles
Journals
News
Advanced Search
Top Searches
2D MaterialsTransformation opticsQuantum PhotonicsSmall lasersSemiconductor UV PhotonicsSupersymmetric microring laser arrays

Acta Optica Sinica, Volume. 39, Issue 1, 0115005(2019)

Point Cloud Registration Based on Multi-Dimensional Mixed Cauchy Distribution

Zhirong Tang1、*, Mingzhe Liu1,3、*, Chang Wang2, and Yue Jiang2
Author Affiliations
  • 1 College of Nuclear Technology and Automation Engineering, Chengdu University of Technology, Chengdu, Sichuan 610059, China
  • 2 College of Electrical Engineering and Information Technology, Sichuan University, Chengdu, Sichuan 610065, China
  • 3 Provincial Key Laboratory of Applied Nuclear Techniques in Geosciences, Chengdu University of Technology, Chengdu, Sichuan 610059, China
    • show less
    AbstractGet PDF(in Chinese)
    Figures&Tables (17)
    Equations (0)
    References (0)
    Cited By (6)
    Tools
    Paper Information
    Topics
    Figures & Tables(17)
    Initial states of point clouds of (a) Bunny and (b) Elephant

    Fig. 1. Initial states of point clouds of (a) Bunny and (b) Elephant

    Download full size
    Corresponding relationship between two point clouds after registration

    Fig. 2. Corresponding relationship between two point clouds after registration

    Download full size
    Corresponding relationship of Bunny point cloud after registration

    Fig. 3. Corresponding relationship of Bunny point cloud after registration

    Download full size
    Corresponding relationship of Elephant point cloud after registration

    Fig. 4. Corresponding relationship of Elephant point cloud after registration

    Download full size
    Corresponding relationship of Bunny point cloud after registration for each algorithm. (a) Registration with data-missing of 25%; (b) registration with data-missing of 50%; (c) registration with data-missing of 75%

    Fig. 5. Corresponding relationship of Bunny point cloud after registration for each algorithm. (a) Registration with data-missing of 25%; (b) registration with data-missing of 50%; (c) registration with data-missing of 75%

    Download full size
    Corresponding relationship of Elephant point cloud after registration for each algorithm. (a) Registration with data-missing of 25%; (b) registration with data-missing of 50%; (c) registration with data-missing of 75%

    Fig. 6. Corresponding relationship of Elephant point cloud after registration for each algorithm. (a) Registration with data-missing of 25%; (b) registration with data-missing of 50%; (c) registration with data-missing of 75%

    Download full size
    RMSE for six registration algorithms. (a) Bunny point cloud; (b) Elephant point cloud

    Fig. 7. RMSE for six registration algorithms. (a) Bunny point cloud; (b) Elephant point cloud

    Download full size
    RMSE for six registration algorithms. (a) Bunny point cloud; (b) Elephant point cloud

    Fig. 8. RMSE for six registration algorithms. (a) Bunny point cloud; (b) Elephant point cloud

    Download full size
    Initial states of point clouds of (a) Bunny and (b) Elephant

    Fig. 9. Initial states of point clouds of (a) Bunny and (b) Elephant

    Download full size
    Corresponding relationship between two point clouds after registration. (a)(b) Bunny point cloud; (c)(d) Elephant point cloud

    Fig. 10. Corresponding relationship between two point clouds after registration. (a)(b) Bunny point cloud; (c)(d) Elephant point cloud

    Download full size
    Two sets of physical maps. (a) Box A; (b) box B

    Fig. 11. Two sets of physical maps. (a) Box A; (b) box B

    Download full size
    Initial states of two sets of scanning data. (a) Box A; (b) box B

    Fig. 12. Initial states of two sets of scanning data. (a) Box A; (b) box B

    Download full size
    Registration results of box A point cloud

    Fig. 13. Registration results of box A point cloud

    Download full size
    Registration results of box B point cloud

    Fig. 14. Registration results of box B point cloud

    Download full size

    • Table 1. RMSE for six registration algorithms

      View table

      Table 1. RMSE for six registration algorithms

      Point cloudRMSE /mm
      MMCGA+Scale-ICPGA+ICPGo-ICPGOGMACPD
      Bunny0.23720.23880.23870.23540.23850.3078
      Elephant0.03160.04920.03160.16570.05740.0213

    • Table 2. RMSE for two registration algorithms

      View table

      Table 2. RMSE for two registration algorithms

      AlgorithmRMSE /mm
      BunnyElephant
      MMC0.22510.0406
      Scale-ICP0.36650.0508

    • Table 3. RMSE for six registration algorithms

      View table

      Table 3. RMSE for six registration algorithms

      Point cloudRMSE /mm
      MMCMMC+ICPMMC+Scale-ICPGo-ICPGOGMACPD
      Box A0.25730.257714.46542.0629×10-50.25040.9703
      Box B0.58020.58860.60960.58170.58973.0836
    Tools

    Get Citation

    Copy Citation Text

    Zhirong Tang, Mingzhe Liu, Chang Wang, Yue Jiang. Point Cloud Registration Based on Multi-Dimensional Mixed Cauchy Distribution[J]. Acta Optica Sinica, 2019, 39(1): 0115005

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Set citation alerts for article
    Save article for my favorites
    Paper Information

    Category: Machine Vision

    Received: Jul. 23, 2018

    Accepted: Sep. 10, 2018

    Published Online: May. 10, 2019

    The Author Email:

    DOI:10.3788/AOS201939.0115005

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology