• Chinese Optics Letters
  • Vol. 18, Issue 6, 061001 (2020)
Qishu Qian1、2, Yihua Hu1、2、*, Nanxiang Zhao1、2, Minle Li1、2, Fucai Shao3, and Xinyuan Zhang1、2
Author Affiliations
  • 1State Key Laboratory of Pulsed Power Laser Technology, National University of Defense Technology, Hefei 230037, China
  • 2Anhui Provincial Key Laboratory of Electronic Restriction, National University of Defense Technology, Hefei 230037, China
  • 3The Military Representative Bureau of the Ministry of Equipment Development, Central Military Commission in Beijing, Beijing 100191, China
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    DOI: 10.3788/COL202018.061001 Cite this Article Set citation alerts
    Qishu Qian, Yihua Hu, Nanxiang Zhao, Minle Li, Fucai Shao, Xinyuan Zhang. Object tracking method based on joint global and local feature descriptor of 3D LIDAR point cloud[J]. Chinese Optics Letters, 2020, 18(6): 061001 Copy Citation Text show less
    Proposed object tracking method of point cloud based on JGLF.
    Fig. 1. Proposed object tracking method of point cloud based on JGLF.
    Flow chart of the proposed object tracking method.
    Fig. 2. Flow chart of the proposed object tracking method.
    Comparison of the object recognition rate at different distances between LIDAR and the object.
    Fig. 3. Comparison of the object recognition rate at different distances between LIDAR and the object.
    Results of the PF point cloud tracking algorithm based on JGLF in frame n: (a) n=1, (b) n=61, (c) n=121, (d) n=181, and (e) n=241. (f) Comparison between particles in frame 186.
    Fig. 4. Results of the PF point cloud tracking algorithm based on JGLF in frame n: (a) n=1, (b) n=61, (c) n=121, (d) n=181, and (e) n=241. (f) Comparison between particles in frame 186.
    Comparison of the object tracking effect between the two algorithms.
    Fig. 5. Comparison of the object tracking effect between the two algorithms.
    Object Recognition Rate (%)Average Running Time (ms)
    MeanStandard Deviation
    FPFH62.3713.175
    VFH64.3411.253.6
    CVFH68.917.794.5
    GRSD39.8516.2831
    ESF87.5916.7139
    JGLF72.0910.816
    Table 1. Object Recognition Ability Comparison of Six Descriptors
    Tracking Accuracy (%)R of Single Frame (%)Average Running Time (ms)CPU Utilized Percent (%)
    MeanStandard Deviation
    Basic algorithm84.8772.8117.7512.445
    Algorithm based on FPFH89.0480.6712.4712.717
    Algorithm based on VFH90.7682.2114.5912.687
    Algorithm based on CVFH91.2580.339.0712.828
    Proposed algorithm98.8288.0111.9612.968
    Table 2. Comparison of Tracking Results of Five Algorithms
    Qishu Qian, Yihua Hu, Nanxiang Zhao, Minle Li, Fucai Shao, Xinyuan Zhang. Object tracking method based on joint global and local feature descriptor of 3D LIDAR point cloud[J]. Chinese Optics Letters, 2020, 18(6): 061001
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