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    Journals >Laser & Optoelectronics Progress >Volume 60 >Issue 12 >Page 1210023 > Article
    • Laser & Optoelectronics Progress
    • Vol. 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
    • show less
    DOI: 10.3788/LOP221735 Cite this Article Set citation alerts
    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 Copy Citation Text show less
    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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    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 1. Point cloud data information
    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 2. RMSE 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 3. Time for each registration algorithm with different scaling factors
    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 4. RMSE 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
    Table 5. Time of the proposed algorithm under different noise
    Abstract
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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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