• Acta Optica Sinica
  • Vol. 37, Issue 11, 1115002 (2017)
Fucai Yang, Dedong Yang*, Ning Mao, and Xueqing Li
Author Affiliations
  • School of Control Science and Engineering, Hebei University of Technology, Tianjin 300130, China
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    DOI: 10.3788/AOS201737.1115002 Cite this Article Set citation alerts
    Fucai Yang, Dedong Yang, Ning Mao, Xueqing Li. Robust Infrared Target Tracking Based on Histograms of Sparse Coding[J]. Acta Optica Sinica, 2017, 37(11): 1115002 Copy Citation Text show less
    Flow chart of overall algorithm
    Fig. 1. Flow chart of overall algorithm
    Dictionaries learned through K-SVD algorithm for three patch sizes
    Fig. 2. Dictionaries learned through K-SVD algorithm for three patch sizes
    Process of computing HSC
    Fig. 3. Process of computing HSC
    Precision plot of different algorithms tested on 20 sequences
    Fig. 4. Precision plot of different algorithms tested on 20 sequences
    Success rate plot of different algorithms tested on 20 sequences
    Fig. 5. Success rate plot of different algorithms tested on 20 sequences
    Precision plots of all attributions. (a) Illumination variation; (b) out-of-plane rotation; (c) scale variation; (d) deformation; (e) occlusion; (f) motion blur; (g) fast motion; (h) in-plane rotation; (i) out of view; (j) background clutter; (k) low resolution
    Fig. 6. Precision plots of all attributions. (a) Illumination variation; (b) out-of-plane rotation; (c) scale variation; (d) deformation; (e) occlusion; (f) motion blur; (g) fast motion; (h) in-plane rotation; (i) out of view; (j) background clutter; (k) low resolution
    Success rate plots of all attributions. (a) Illumination variation; (b) out-of-plane rotation; (c) occlusion; (d) scale variation; (e) deformation; (f) fast motion; (g) motion blur; (h) in-plane rotation; (i) background clutter; (j) out of view; (k) low resolution
    Fig. 7. Success rate plots of all attributions. (a) Illumination variation; (b) out-of-plane rotation; (c) occlusion; (d) scale variation; (e) deformation; (f) fast motion; (g) motion blur; (h) in-plane rotation; (i) background clutter; (j) out of view; (k) low resolution
    Tracking results of the proposed algorithm and another nine trackers on nine image sequences. (a) Out-of-plane rotation (birds and running_rhino sequences); (b) deformation (birds and crouching sequences); (c) background clutter (crowd and mixed_distractors sequences); (d) occlusion (street and hiding sequences); (d) scale variation (jacket and selma sequences)
    Fig. 8. Tracking results of the proposed algorithm and another nine trackers on nine image sequences. (a) Out-of-plane rotation (birds and running_rhino sequences); (b) deformation (birds and crouching sequences); (c) background clutter (crowd and mixed_distractors sequences); (d) occlusion (street and hiding sequences); (d) scale variation (jacket and selma sequences)
    Fucai Yang, Dedong Yang, Ning Mao, Xueqing Li. Robust Infrared Target Tracking Based on Histograms of Sparse Coding[J]. Acta Optica Sinica, 2017, 37(11): 1115002
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