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At present the visual tracking model based on sparse representation is mainly divided into two types: one is to use the template set to reconstruct candidate samples, which is called forward model; the other is to project the template set into a candidate space, which is called reverse model. What the two models have in common is to compute the sparse correlation coefficient matrix of candidate sample and template set. Based on this, the paper establishes a bidirectional cooperative sparse representation tracking model. Using L2-norm constraint item, the forward and reverse sparse correlation matrix coefficients could be uniformly convergent. In comparison to conventional unidirectional sparse tracking model, bidirectional sparse tracking model could fully excavate the sparse mapping relation of the whole candidate sample and template set. And the candidate that scores highest in the sparse mapping table for the positive and negative templates is the tracking result. Based on the accelerated proximal gradient fast method, the paper derives the optimum solution (in matrix form) of bidirectional sparse tracking model. As a result, it allows the candidates and templates to be calculated in parallel, which can improve the calculation efficiency to some extent. Numerical examples show that the proposed tracking algorithm has certain priority over against the conventional unidirectional sparse tracking methods.
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Keywords:
- sparse representation /
- visual tracking /
- Bayesian framework
[1] Gao W, Tang Y, Zhu M 2014 Acta Phys. Sin. 63 094204 (in Chinese) [高文, 汤洋, 朱明 2014 63 094204]
[2] Donoho D L 2006 IEEE Trans. Inform. Theory 52 1289
[3] Wright J, Yang A Y, Ganesh A, Sastry S S, Ma Y 2009 IEEE Trans. Pattern Anal. Mach. Intell. 31 210
[4] Deng C Z, Tian W, Chen P, Wang S Q, Zhu H S, Hu S F 2014 Acta Phys. Sin. 63 044202 (in Chinese) [邓承志, 田伟, 陈盼, 汪胜前, 朱华生, 胡赛凤 2014 63 044202]
[5] Song C X, Ma K, Qin C, Xiao P 2013 Acta Phys. Sin. 62 040702 (in Chinese) [宋长新, 马克, 秦川, 肖鹏 2013 62 040702]
[6] Mei X, Ling H B 2011 IEEE Trans. Pattern Anal. Mach. Intell. 33 2259
[7] Bao C L, Wu Y, Ling H B, Ji H 2012 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Providence, USA, June 16-21, 2012 p1830
[8] Zhong W, Lu H C, Yang M H 2012 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Providence, USA, June 16-21, 2012 p1838
[9] Liu H P, Sun F C 2010 Proceedings of IEEE 20th Conference on Pattern Recognition Istanbul, Turkey, August 23-26, 2010 p1702
[10] Zhuang B H, Lu H C, Xiao Z Y, Wang D 2014 IEEE Trans. Image Proc. 23 1872
[11] Li X, Hu W M, Shen C H, Zhang Z F, Dick A 2013 ACM Trans. Intell. Syst. Technol. 4 58
[12] Toh K C, Yun S 2010 Pac. J. Optim. 6 615
[13] Zhang K H, Zhang L, Yang M H 2012 Proceedings of European Conference on Computer Vision Berlin, Germany, October 7-13, 2012 p864
[14] Babenko B, Yang M H, Belongie S 2011 IEEE Trans. Pattern Anal. Mach. Intell. 33 1619
[15] Wu Y, Lim J, Yang M H 2013 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Portland, USA, June 23-28, 2013 p2411
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[1] Gao W, Tang Y, Zhu M 2014 Acta Phys. Sin. 63 094204 (in Chinese) [高文, 汤洋, 朱明 2014 63 094204]
[2] Donoho D L 2006 IEEE Trans. Inform. Theory 52 1289
[3] Wright J, Yang A Y, Ganesh A, Sastry S S, Ma Y 2009 IEEE Trans. Pattern Anal. Mach. Intell. 31 210
[4] Deng C Z, Tian W, Chen P, Wang S Q, Zhu H S, Hu S F 2014 Acta Phys. Sin. 63 044202 (in Chinese) [邓承志, 田伟, 陈盼, 汪胜前, 朱华生, 胡赛凤 2014 63 044202]
[5] Song C X, Ma K, Qin C, Xiao P 2013 Acta Phys. Sin. 62 040702 (in Chinese) [宋长新, 马克, 秦川, 肖鹏 2013 62 040702]
[6] Mei X, Ling H B 2011 IEEE Trans. Pattern Anal. Mach. Intell. 33 2259
[7] Bao C L, Wu Y, Ling H B, Ji H 2012 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Providence, USA, June 16-21, 2012 p1830
[8] Zhong W, Lu H C, Yang M H 2012 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Providence, USA, June 16-21, 2012 p1838
[9] Liu H P, Sun F C 2010 Proceedings of IEEE 20th Conference on Pattern Recognition Istanbul, Turkey, August 23-26, 2010 p1702
[10] Zhuang B H, Lu H C, Xiao Z Y, Wang D 2014 IEEE Trans. Image Proc. 23 1872
[11] Li X, Hu W M, Shen C H, Zhang Z F, Dick A 2013 ACM Trans. Intell. Syst. Technol. 4 58
[12] Toh K C, Yun S 2010 Pac. J. Optim. 6 615
[13] Zhang K H, Zhang L, Yang M H 2012 Proceedings of European Conference on Computer Vision Berlin, Germany, October 7-13, 2012 p864
[14] Babenko B, Yang M H, Belongie S 2011 IEEE Trans. Pattern Anal. Mach. Intell. 33 1619
[15] Wu Y, Lim J, Yang M H 2013 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Portland, USA, June 23-28, 2013 p2411
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