基于判别性局部联合稀疏模型的多任务跟踪

黄丹丹; 孙怡; 黄丹丹; 孙怡

doi:10.16383/j.aas.2016.c150416

[1]

Yilmaz A, Javed O, Shah M. Object tracking:a survey. ACM Computing Surveys (CSUR), 2006, 38(4):Article No. 13

[2]

Wu Y, Lim J, Yang M H. Online object tracking:a benchmark. In:Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition. Portland, USA:IEEE, 2013. 2411-2418

[3]

Smeulders A W M, Chu D M, Cucchiara R, Calderara S, Dehghan A, Shah M. Visual tracking:an experimental survey. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2014, 36(7):1442-1468 doi: 10.1109/TPAMI.2013.230

[4]

Adam A, Rivlin E, Shimshoni I. Robust fragments-based tracking using the integral histogram. In:Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. New York, USA:IEEE, 2006. 798-805

[5]

Kwon J, Lee K M. Visual tracking decomposition. In:Proceedings of the 2010 IEEE Conference on Computer Vision and Pattern Recognition. San Francisco, USA:IEEE, 2010. 1269-1276

[6]

Ross D A, Lim J, Lin R S, Yang M H. Incremental learning for robust visual tracking. International Journal of Computer Vision, 2008, 77(1-3):125-141 doi: 10.1007/s11263-007-0075-7

[7]

Babenko B, Yang M H, Belongie S. Visual tracking with online multiple instance learning. In:Proceedings of the 2009 IEEE Conference on Computer Vision and Pattern Recognition. Miami FL, USA:IEEE, 2009. 983-990

[8]

Kalal Z, Matas J, Mikolajczyk K. P-N learning:bootstrapping binary classifiers by structural constraints. In:Proceedings of the 2010 IEEE Conference on Computer Vision and Pattern Recognition. San Francisco, USA:IEEE, 2010. 49-56

[9]

Mei X, Ling H B. Robust visual tracking using L₁ minimization. In:Proceedings of the 12th IEEE International Conference on Computer Vision. Kyoto, Japan:IEEE, 2009. 1436-1443

[10]

Bao C L, Wu Y, Ling H B, Ji H. Real time robust L₁ tracker using accelerated proximal gradient approach. In:Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition. Providence, USA:IEEE, 2012. 1830-1837

[11]

Zhang S P, Yao H X, Zhou H Y, Sun X, Liu S H. Robust visual tracking based on online learning sparse representation. Neurocomputing, 2013, 100:31-40 doi: 10.1016/j.neucom.2011.11.031

[12]

Wang D, Lu H C, Yang M H. Online object tracking with sparse prototypes. IEEE Transactions on Image Processing, 2013, 22(1):314-325 doi: 10.1109/TIP.2012.2202677

[13]

Wang L F, Yan H P, Lv K, Pan C H. Visual tracking via kernel sparse representation with multikernel fusion. IEEE Transactions on Circuits and Systems for Video Technology, 2014, 24(7):1132-1141 doi: 10.1109/TCSVT.2014.2302496

[14]

Liu B Y, Huang J Z, Yang L, Kulikowsk C. Robust tracking using local sparse appearance model and k-selection. In:Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition. Providence, USA:IEEE, 2011. 1313-1320

[15]

Jia X, Lu H C, Yang M H. Visual tracking via adaptive structural local sparse appearance model. In:Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition. Providence, USA:IEEE, 2012. 1822-1829

[16]

Xie Y, Zhang W S, Li C H, Lin S Y, Qu Y Y, Zhang Y H. Discriminative object tracking via sparse representation and online dictionary learning. IEEE Transactions on Cybernetics, 2014, 44(4):539-553 doi: 10.1109/TCYB.2013.2259230

[17]

Zhong W, Lu H C, Yang M H. Robust object tracking via sparsity-based collaborative model. In:Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition. Providence, USA:IEEE, 2012. 1838-1845

[18]

Zhang T Z, Ghanem B, Liu S, Ahuja N. Robust visual tracking via multi-task sparse learning. In:Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition. Providence, USA:IEEE, 2012. 2042-2049

[19]

Hong Z B, Mei X, Prokhorov D, Tao D C. Tracking via robust multi-task multi-view joint sparse representation. In:Proceedings of the 2013 IEEE International Conference on Computer Vision. Sydney, NSW:IEEE, 2013. 649-656

[20]

Dong W H, Chang F L, Zhao Z J. Visual tracking with multifeature joint sparse representation. Journal of Electronic Imaging, 2015, 24(1):013006 doi: 10.1117/1.JEI.24.1.013006

[21]

Zhuang B H, Lu H C, Xiao Z Y, Wang D. Visual tracking via discriminative sparse similarity map. IEEE Transactions on Image Processing, 2014, 23(4):1872-1881 doi: 10.1109/TIP.2014.2308414

[22]

Zhang T Z, Liu S, Xu C S, Yan S C, Ghanem B, Ahuja N, Yang M H. Structural sparse tracking. In:Proceedings of the 2015 IEEE Conference on Computer Vision and Pattern Recognition. Boston, MA, USA:IEEE, 2015. 150-158

[23]

王梦.基于复合稀疏模型的多任务视频跟踪算法研究[硕士学位论文], 上海交通大学, 中国, 2014.

Wang Meng. Multi-Task Visual Tracking Using Composite Sparse Model[Master dissertation], Shanghai Jiao Tong University, China, 2014.

[24]

Yuan X T, Liu X B, Yan S C. Visual classification with multitask joint sparse representation. IEEE Transactions on Image Processing, 2012, 21(10):4349-4360 doi: 10.1109/TIP.2012.2205006

[25]

Doucet A, de Freitas N, Gordon N. Sequential Monte Carlo Methods in Practice. New York:Springer-Verlag, 2001.

[26]

Zhang T Z, Liu S, Ahuja N, Yang M H, Ghanem B. Robust visual tracking via consistent low-rank sparse learning. International Journal of Computer Vision, 2015, 111(2):171-190 doi: 10.1007/s11263-014-0738-0