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Laser & Optoelectronics Progress, Volume. 60, Issue 12, 1210023(2023)

Registration Algorithm for Differently Scaled Point Clouds Based on Artificial Bee Colony Optimization

Yiping Fan1,2, Baozhen Ge1,2, and Lei Chen3、*
Author Affiliations
  • 1School of Precision Instrument and Opto-Electronics Engineering, Tianjin University, Tianjin 300072, China
  • 2Key Laboratory of Opto-Electronic Information and Technology, Ministry of Education, Tianjin 300072, China
  • 3School of Information Engineering, Tianjin University of Commerce, Tianjin 300134, China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (16)
    Equations (13)
    References (19)
    Cited By (1)
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    Figures & Tables(16)
    Flowchart of proposed algorithm

    Fig. 1. Flowchart of proposed algorithm

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    Homologous point cloud data. (a) Bun000; (b) Bun045; (c) ArmadilloBack_0; (d) ArmadilloBack_30

    Fig. 2. Homologous point cloud data. (a) Bun000; (b) Bun045; (c) ArmadilloBack_0; (d) ArmadilloBack_30

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    Cross-source point cloud data. (a) Bag_Kinect; (b) Bag_SFM; (c) Tsinghua gate_Lidar; (d) Tsinghua gate_SFM; (e) Life science building_Lidar; (f) Life science building_SFM

    Fig. 3. Cross-source point cloud data. (a) Bag_Kinect; (b) Bag_SFM; (c) Tsinghua gate_Lidar; (d) Tsinghua gate_SFM; (e) Life science building_Lidar; (f) Life science building_SFM

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    Point clouds to be registered with different scaling factors. (a) Bunny, so=20; (b) Bunny, so=10; (c) Bunny, so=1.25; (d) Armadillo, so=20; (e) Armadillo, so=10; (f) Armadillo, so=1.25

    Fig. 4. Point clouds to be registered with different scaling factors. (a) Bunny, so=20; (b) Bunny, so=10; (c) Bunny, so=1.25; (d) Armadillo, so=20; (e) Armadillo, so=10; (f) Armadillo, so=1.25

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    Registration results of various algorithms for Bunny point cloud under different scale factors. (a) EBABC-RS-IR; (b) ICP; (c) Scale-ICP; (d) CPD; (e) proposed algorithm

    Fig. 5. Registration results of various algorithms for Bunny point cloud under different scale factors. (a) EBABC-RS-IR; (b) ICP; (c) Scale-ICP; (d) CPD; (e) proposed algorithm

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    Registration results of various algorithms for Armadillo point cloud under different scale factors. (a) EBABC-RS-IR; (b) ICP; (c) Scale-ICP; (d) CPD; (e) proposed algorithm

    Fig. 6. Registration results of various algorithms for Armadillo point cloud under different scale factors. (a) EBABC-RS-IR; (b) ICP; (c) Scale-ICP; (d) CPD; (e) proposed algorithm

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    Point cloud registration results under different noise. (a) Bunny, 20 dB; (b) Bunny, 25 dB; (c) Bunny, 30 dB; (d) Armadillo, 20 dB; (e) Armadillo, 25 dB; (f) Armadillo, 30 dB

    Fig. 7. Point cloud registration results under different noise. (a) Bunny, 20 dB; (b) Bunny, 25 dB; (c) Bunny, 30 dB; (d) Armadillo, 20 dB; (e) Armadillo, 25 dB; (f) Armadillo, 30 dB

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    Relative initial state of cross-source point clouds to be registered. (a) Bag; (b) Tsinghua gate; (c) Life science building

    Fig. 8. Relative initial state of cross-source point clouds to be registered. (a) Bag; (b) Tsinghua gate; (c) Life science building

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    Local amplification effect of Bag registration

    Fig. 9. Local amplification effect of Bag registration

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    Tsinghua gate point cloud registration results. (a) Main perspective; (b) prone perspective; (c) side perspective

    Fig. 10. Tsinghua gate point cloud registration results. (a) Main perspective; (b) prone perspective; (c) side perspective

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    Life science building point cloud registration results. (a) Main perspective; (b) prone perspective; (c) side perspective

    Fig. 11. Life science building point cloud registration results. (a) Main perspective; (b) prone perspective; (c) side perspective

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    • Table 1. Point cloud data information

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      Table 1. Point cloud data information

      Point cloudImage to be registeredTarget /source point cloudNumber of pointsAngle of view
      BunnyBun000Target4025645°
      Bun045Source40097
      ArmadilloArmadilloBack_0Target1928330°
      ArmadilloBack_30Source12150
      BagBag_KinectTarget11595Unknown
      Bag_SFMSource21495
      Tsinghua gateTsinghua gate_LidarTarget33721Unknown
      Tsinghua gate_SFMSource971436
      Life science buildingLife science building _LidarTarget761729Unknown
      Life science building _SFMSource1813056

    • Table 2. RMSE for each registration algorithm with different scaling factors

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      Table 2. RMSE for each registration algorithm with different scaling factors

      Point cloudsoScale-ICPCPDProposed algorithm
      Bunny201.425×10-22.127×10-31.970×10-3
      101.425×10-22.138×10-32.086×10-3
      1.251.425×10-22.152×10-31.985×10-3
      Armadillo201.503×10-21.652×10-28.525×10-3
      101.503×10-21.663×10-27.763×10-3
      1.251.503×10-21.629×10-27.758×10-3

    • Table 3. Time for each registration algorithm with different scaling factors

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      Table 3. Time for each registration algorithm with different scaling factors

      Point cloudsoScale-ICPCPDProposed algorithm
      Bunny2044.28091.11017.120
      1043.44991.47017.670
      1.2543.45288.92816.852
      Armadillo209.62912.57712.335
      109.30615.45711.416
      1.259.59813.49914.477

    • Table 4. RMSE of the proposed algorithm under different noise

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      Table 4. RMSE of the proposed algorithm under different noise

      Point cloudso20 dB25 dB30 dBNo noise
      Bunny208.229×10-34.594×10-33.799×10-31.970×10-3
      107.949×10-37.176×10-33.223×10-32.086×10-3
      1.258.358×10-34.704×10-33.073×10-31.985×10-3
      Armadillo201.010×10-28.815×10-38.034×10-38.525×10-3
      101.032×10-21.129×10-28.155×10-37.763×10-3
      1.251.184×10-28.804×10-38.312×10-37.758×10-3

    • Table 5. Time of the proposed algorithm under different noise

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      Table 5. Time of the proposed algorithm under different noise

      Point cloudso20 dB25 dB30 dBNo noise
      Bunny2020.27920.87919.43217.120
      1020.28920.09920.60417.670
      1.2520.61719.99717.41916.852
      Armadillo2014.04514.77414.30812.335
      1014.93114.57013.65411.416
      1.2514.09814.82613.95614.477
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    Yiping Fan, Baozhen Ge, Lei Chen. Registration Algorithm for Differently Scaled Point Clouds Based on Artificial Bee Colony Optimization[J]. Laser & Optoelectronics Progress, 2023, 60(12): 1210023

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    Paper Information

    Category: Image Processing

    Received: May. 30, 2022

    Accepted: Jul. 14, 2022

    Published Online: Jun. 1, 2023

    The Author Email: Chen Lei (chenlei@tjcu.edu.cn)

    DOI:10.3788/LOP221735

    Topics

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