A Survey: Target Tracking Algorithm Based on Sparse Representation

2014 ◽  
Author(s):  
Dan Lu ◽  
Linsheng Li ◽  
Qingsen Yan
Keyword(s):  
Sparse Representation ◽  
Target Tracking ◽  
Tracking Algorithm

scholarly journals Unmanned Aerial Vehicle Video-Based Target Tracking Algorithm Using Sparse Representation

2019 ◽  
Vol 6 (6) ◽  
pp. 9689-9706 ◽  
Author(s):  
Minjie Wan ◽  
Guohua Gu ◽  
Weixian Qian ◽  
Kan Ren ◽  
Xavier Maldague ◽  
...  
Keyword(s):  
Sparse Representation ◽  
Target Tracking ◽  
Unmanned Aerial Vehicle ◽  
Tracking Algorithm ◽  
Aerial Vehicle

Dim moving target tracking algorithm based on particle discriminative sparse representation

2016 ◽  
Vol 75 ◽  
pp. 100-106 ◽  
Author(s):  
Zhengzhou Li ◽  
Jianing Li ◽  
Fengzeng Ge ◽  
Wanxing Shao ◽  
Bing Liu ◽  
...  
Keyword(s):  
Sparse Representation ◽  
Target Tracking ◽  
Tracking Algorithm ◽  
Moving Target ◽  
Moving Target Tracking

scholarly journals Feature Selection Tracking Algorithm Based on Sparse Representation

2015 ◽  
Vol 2015 ◽  
pp. 1-9
Author(s):  
Hui-dong Lou ◽  
Wei-guang Li ◽  
Yue-en Hou ◽  
Qing-he Yao ◽  
Guo-qiang Ye ◽  
...  
Keyword(s):  
Feature Selection ◽  
Sparse Representation ◽  
Target Tracking ◽  
Visual Tracking ◽  
Fast Algorithm ◽  
The State ◽  
Tracking Algorithm ◽  
Complex Environment

In order to enhance the robustness of visual tracking algorithm in complex environment, a novel visual tracking algorithm based on multifeature selection and sparse representation is proposed. In the framework of particles filter, particles with low target similarity are first filtered out by a fast algorithm; then, based on the principle of sparsely reconstructing the sample label, the features with high differentiation against the background are involved in the computation so as to reduce the disturbance of occlusions and noises. Finally, candidate targets are linearly reconstructed via sparse representation and the sparse equation is solved by using APG method to obtain the state of the target. Four comparative experiments demonstrate that the proposed algorithm in this paper has effectively improved the robustness of the target tracking algorithm.

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