• Laser & Optoelectronics Progress
  • Vol. 58, Issue 16, 1615004 (2021)
Qi Xu1, Junbo Han1、2、*, and Haixia Li2、3
Author Affiliations
  • 1College of Information Engineering, Chaohu University, Hefei, Anhui 230031, China
  • 2College of Computer Science and Technology/College of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu 211106, China
  • 3Zhejiang Police Vocational Academy, Hangzhou, Zhejiang 310018, China
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    DOI: 10.3788/LOP202158.1615004 Cite this Article Set citation alerts
    Qi Xu, Junbo Han, Haixia Li. Convolution-Based Sparse Tracking Algorithm[J]. Laser & Optoelectronics Progress, 2021, 58(16): 1615004 Copy Citation Text show less
    Feature diagram of layered structure based on convolution sparse surface model
    Fig. 1. Feature diagram of layered structure based on convolution sparse surface model
    Relationship between the Mmeasurevalue and corresponding occluded target
    Fig. 2. Relationship between the Mmeasurevalue and corresponding occluded target
    Precision and success plots of 10 sparse tracking algorithms on OTB100. (a) Precision plot; (b) success plot
    Fig. 3. Precision and success plots of 10 sparse tracking algorithms on OTB100. (a) Precision plot; (b) success plot
    Precision plots of 10 sparse tracking algorithms in different challenge attributes
    Fig. 4. Precision plots of 10 sparse tracking algorithms in different challenge attributes
    Success plots of 10 sparse tracking algorithms in different challenge attributes
    Fig. 5. Success plots of 10 sparse tracking algorithms in different challenge attributes
    Experimental results of 10 sparse tracking algorithms in some video sequences at OTB100 video set
    Fig. 6. Experimental results of 10 sparse tracking algorithms in some video sequences at OTB100 video set
    Qi Xu, Junbo Han, Haixia Li. Convolution-Based Sparse Tracking Algorithm[J]. Laser & Optoelectronics Progress, 2021, 58(16): 1615004
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