Infrared and Laser Engineering, Volume. 49, Issue 11, 20200284(2020)

Tracking of dense group targets based on motion grouping

Lei Zhang1... Shuai Zhu2, Tianyu Liu2 and Yuehuan Wang2 |Show fewer author(s)
Author Affiliations
  • 1Beijing Institute of Surveying and Communication, Beijing 100089, China
  • 2School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China
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    Figures & Tables(18)
    Flowchart of the proposed algorithm
    Dividing dense target into sparse groups
    Non-neighbor individuals in cluster motion
    Relationship between and 与路径长度规模关系图
    Relationship between and with regularization factor引入正则化因子后与路径长度规模关系图
    Distribution of group target and extracted optical flow
    Divided group result according to motion patten
    Directed graph model for target group
    Result of marked potential target in target group
    Track of potential target in target group
    Grouping performance comparison
    Real-time performance comparison
    • Table 1.

      Result of collectiveness matrix

      聚集度矩阵结果

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      Table 1.

      Result of collectiveness matrix

      聚集度矩阵结果

      Node123415
      10.0040.0260.039−0.27−0.06
      20.0240.0120.0570.087−0.05
      30.0360.0580.0110.004−0.03
      4−0.010.0900.004−0.03−0.05
      15−0.03−0.06−0.08−0.030.011
    • Table 2.

      Result of adjacency matrix for directed graph

      有向图邻接矩阵结果

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      Table 2.

      Result of adjacency matrix for directed graph

      有向图邻接矩阵结果

      Node123415
      100000
      200100
      300000
      401000
      1500000
    • Table 3.

      Tracking result without interframe suppression false alarm

      未采用帧间虚警抑制跟踪结果

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      Table 3.

      Tracking result without interframe suppression false alarm

      未采用帧间虚警抑制跟踪结果

      DataFrame that does not meet condition 1Frame that does not meet condition 2Accuracy
      121,4,6,8,12,14,177,9,12,16,20,23,2757,61,6255,59,60,610.8460.831
      34,8,12,13,16,17,1852,59,600.846
      45,9,18,22,3131,40,45,550.861
      59,10,11,20,20,2644,49,630.877
    • Table 4.

      Tracking result with interframe suppression false alarm

      采用帧间虚警抑制跟踪结果

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      Table 4.

      Tracking result with interframe suppression false alarm

      采用帧间虚警抑制跟踪结果

      DataFrame that does not meet condition 1Frame that does not meet condition 2Accuracy
      121,4,6,8,147,9,12,16,2361,6259,60,610.8920.877
      312,13,16,17,1859,600.892
      45,3131, 45,550.923
      59,10,1136,49,630.907
    • Table 5. Dual suppression matrix 对偶抑制矩阵

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      Table 5. Dual suppression matrix 对偶抑制矩阵

      Node123415
      10.0020.0390.049−0.01−0.05
      20.0360.0100.0570.022−0.05
      30.0440.0520.0100.002−0.02
      4-0.010.0200.004−0.02−0.04
      15−0.03−0.03−0.06−0.030.013
    • Table 6. Dual suppression matrix 对偶抑制矩阵

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      Table 6. Dual suppression matrix 对偶抑制矩阵

      Node123415
      10.0040.0520.049−0.02−0.06
      20.0500.0120.0570.033−0.07
      30.0460.0580.0160.002−0.03
      4−0.010.0300.004−0.03−0.05
      15−0.03−0.04−0.07−0.040.019
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    Lei Zhang, Shuai Zhu, Tianyu Liu, Yuehuan Wang. Tracking of dense group targets based on motion grouping[J]. Infrared and Laser Engineering, 2020, 49(11): 20200284

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    Paper Information

    Category: Image processing

    Received: Jul. 14, 2020

    Accepted: --

    Published Online: Jan. 4, 2021

    The Author Email:

    DOI:10.3788/IRLA20200284

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