Target tracking technology development combing (Object Tracking) -- Computer Vis

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Target tracking technology development review(Object Tracking)

Sason@CSDN
Does not include the CVPR2013 and after the paper.

1. D. Jepson,D. J. Fleet, and T. F. El-Maraghi. Robust online appearance models for visualtracking. In CVPR, 2001.

2. R. Collins andY. Liu. On-line selection of discriminative tracking features. In ICCV, 2003.

3. R. T. Collins.Mean-shift blob tracking through scale space. In CVPR, 2003.

4. S. Avidan.Ensemble tracking. In CVPR, 2005.

5. J. Lim, D.Ross, R.-S. Lin, and M.-H. Yang. Incremental learning for visual tracking. InNIPS, 2005.

6. A. Adam, E. Rivlin,and I. Shimshoni. Robust fragments-based tracking using the integral histogram.In CVPR, 2006.

7. A. Yilmaz, O. Javed,and M. Shah. Object tracking: A suervey. ACM Computing Surveys, 2006.

8. L. Lu and G.D. Hager. A nonparametric treatment for location/segmentation based visualtracking. In CVPR, 2007.

9. X. Ren and J.Malik. Tracking as repeated figure/ground segmentation. In CVPR, 2007.

10. X. Li, W. Hu,Z. Zhang, X. Zhang, M. Zhu, and J. Cheng. Visual tracking via incrementallog-Euclidean Riemannian subspace learning. In CVPR, 2008.

11. J. Kwon andK. M. Lee. Tracking of a non-rigid object via patch-based dynamic appearance modelingand adaptive Basin Hopping Monte Carlo sampling. In CVPR, 2009.

12. D.-N. Ta,W.-C. Chen, N. Gelfand, and K. Pulli. SURFTrac: Efficient tracking andcontinuous object recognition using local feature descriptors. In CVPR, 2009.

13. B. Babenko,M.-H. Yang, and S. Belongie. Visual tracking with online multiple instancelearning. In CVPR, 2009.

14. X. Mei and H.Ling. Robust visual tracking using l1 minimization. In ICCV, 2009.

15. B. Han, Y.Zhu, D. Comaniciu, and L. S. Davis. Visual tracking by continuous densitypropagation in sequential Bayesian filtering framework. In TPAMI, 2009.

16. J. Kwon andK. M. Lee. Visual tracking decomposition. In CVPR, 2010.

17. J. Santner,C. Leistner, A. Saffari, T. Pock, and H. Bischof. PROST: Parallel robust onlinesimple tracking. In CVPR, 2010.

18. B. Liu, J.Huang, L. Yang, and C. A. Kulikowski. Robust tracking using local sparseappearance model and k-selection. In CVPR, 2011.

19. S.Wang, H.Lu, F. Yang, and M.-H. Yang. Superpixel tracking. In ICCV, 2011.

20. Shu Wang,Huchuan Lu, Fan Yang, and Ming-Hsuan Yang, Superpixel Tracking, In ICCV, 2011.

21. S. Hare, A.Saffari, and P. H. S. Torr. Struck: Structured output tracking with kernels. InICCV, 2011.

22. W. Hu, X. Li,X. Zhang, X. Shi, S. J. Maybank, and Z. Zhang. Incremental tensor subspacelearning and its applications to foreground segmentation and tracking. IJCV, 2011.

23. C. Bao, Y.Wu,H. Ling, and H. Ji. Real time robust 1 tracker using accelerated proximal gradient approach.In CVPR, 2012.

24. X. Jia, H.Lu, and M.-H. Yang. Visual tracking via adaptive structural local sparseappearance model. In CVPR, 2012.

25. W. Zhong, H.Lu, and M.-H. Yang. Robust object tracking via sparsity-based collaborativemodel. In CVPR, 2012.

26. T. Zhang, B.Ghanem, S. Liu, and N. Ahuja. Robust visual tracking via multitask sparselearning. In CVPR, 2012.

27. K. Zhang, L.Zhang, and M.-H. Yang. Real-time compressive tracking. In ECCV, 2012.

28. Z. Kalal, K.Mikolajczyk, and J. Matas. Tracking-learning-detection. TPAMI, 2012.

29. H. Lu, S. Lu,D. Wang, S. Wang, and H. Leung. Pixel-wise spatial pyramid-based

hybrid tracking. TCSVT,2012.

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Posted by Wanda at December 14, 2013 - 6:12 AM