• Laser & Optoelectronics Progress
  • Vol. 58, Issue 16, 1610011 (2021)
Yuanfa Ji1、2, Chuanji He1、2, Xiyan Sun1、2、*, and Ning Guo1、2
Author Affiliations
  • 1Guangxi Key Laboratory of Precision Navigation Technology and Application, Guilin University of Electronic Technology, Guilin, Guangxi 541004, China
  • 2National & Local Joint Engineering Research Center of Satellite Navigation and Location Service, Guilin, Guangxi 541004, China;
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    DOI: 10.3788/LOP202158.1610011 Cite this Article Set citation alerts
    Yuanfa Ji, Chuanji He, Xiyan Sun, Ning Guo. Object Tracking Based on Adaptive Feature Fusion and Context-Aware[J]. Laser & Optoelectronics Progress, 2021, 58(16): 1610011 Copy Citation Text show less
    Flowchart of the proposed algorithm
    Fig. 1. Flowchart of the proposed algorithm
    APCE value and response value at different scenes. (a) Scene 1; (b) scene 2
    Fig. 2. APCE value and response value at different scenes. (a) Scene 1; (b) scene 2
    Color histogram and response map. (a) Original image; (b) color histogram; (c) response map of color feature
    Fig. 3. Color histogram and response map. (a) Original image; (b) color histogram; (c) response map of color feature
    Adaptive weight values for deep and shallow scores
    Fig. 4. Adaptive weight values for deep and shallow scores
    Comparison of tracking performance of three algorithms. (a)Precision; (b)success rate
    Fig. 5. Comparison of tracking performance of three algorithms. (a)Precision; (b)success rate
    Comparison of the precision and success rate of 10 tracking algorithms on OTB-2013 benchmark. (a) Precision; (b) success rate
    Fig. 6. Comparison of the precision and success rate of 10 tracking algorithms on OTB-2013 benchmark. (a) Precision; (b) success rate
    Comparison of tracking precision of 8 attribute sequences on OTB-2013 benchmark
    Fig. 7. Comparison of tracking precision of 8 attribute sequences on OTB-2013 benchmark
    Comparison of tracking success rates of 8 attribute sequences on OTB-2013 benchmark
    Fig. 8. Comparison of tracking success rates of 8 attribute sequences on OTB-2013 benchmark
    Qualitative comparison of 10 tracking algorithms on OTB-2013 benchmark
    Fig. 9. Qualitative comparison of 10 tracking algorithms on OTB-2013 benchmark
    ParameterOURHCFSRDCFStapleLCTSiamFCRPTSAMFKCFDSST
    Tracking speed /(frame·s-1)51047528556817221
    Table 1. Tracking speed of 10 tracking algorithms
    Yuanfa Ji, Chuanji He, Xiyan Sun, Ning Guo. Object Tracking Based on Adaptive Feature Fusion and Context-Aware[J]. Laser & Optoelectronics Progress, 2021, 58(16): 1610011
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