Acta Optica Sinica, Volume. 37, Issue 11, 1115002(2017)
Robust Infrared Target Tracking Based on Histograms of Sparse Coding
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
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
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)
Get Citation
Copy Citation Text
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
Category: Machine Vision
Received: Mar. 27, 2017
Accepted: --
Published Online: Sep. 7, 2018
The Author Email: Yang Dedong (ydd12677@163.com)