Discriminant tracking using tensor representation with semi-supervised improvement

Proceedings of the IEEE International Conference on Computer Vision

Volumn , Issue , 2013, Pages 1569-1576

  Gao, Jin ^a   Xing, Junliang ^a   Hu, Weiming ^a   Maybank, Steve ^b  

^a INSTITUTE OF AUTOMATION   (China)

^b UNIVERSITY OF LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ITERATIVE METHODS;

DISCRIMINANT INFORMATIONS; DOMINANT MECHANISM; GEOMETRICAL STRUCTURE; LINEAR EMBEDDING; NOVEL TECHNIQUES; OBJECT REPRESENTATIONS; SPATIAL CORRELATIONS; TENSOR REPRESENTATION;

TENSORS;

EID: 84898828271     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2013.198     Document Type: Conference Paper

References (35)

1. A. Adam, E. Rivlin, and I. Shimshoni. Robust fragments-based tracking using the integral histogram. In CVPR, 2006.
2. B. Babenko, M. Yang, and S. Belongie. Visual tracking with online multiple instance learning. In CVPR, 2009.
3. C. Bao, Y.Wu, H. Ling, and H. Ji. Real time robust 1 tracker using accelerated proximal gradient approach. In CVPR, 2012.
4. K. P. Bennett, A. Demiriz, and R. Maclin. Exploiting unlabeled data in ensemble methods. In ACM SIGKDD, 2002.
5. H. Grabner, M. Grabner, and H. Bischof. Real-time tracking via on-line boosting. In BMVC, 2006.
6. H. Grabner, C. Leistner, and H. Bischof. Semi-supervised on-line boosting for robust tracking. In ECCV, 2008.
7. X. He, D. Cai, and P. Niyogi. Tensor subspace analysis. In NIPS, 2005.
8. J. Kwon and K. Lee. Visual tracking decomposition. In CVPR, 2010.
9. J. Kwon and K. Lee. Tracking by sampling trackers. In ICCV, 2011.
10. G. Li, L. Qin, Q. Huang, J. Pang, and S. Jiang. Treat samples differently: object tracking with semi-supervised online covboost. In ICCV, 2011.
11. P. Li and Q. Sun. Tensor-based covariance matrices for object tracking. In ICCV Workshops, 2011.
12. X. Li, A. Dick, H. Wang, C. Shen, and A. van den Hengel. Graph mode-based contextual kernels for robust svm tracking. In ICCV, 2011.
13. X. Li, W. Hu, Z. Zhang, X. Zhang, and G. Luo. Robust visual tracking based on incremental tensor subspace learning. In ICCV, 2007.
14. X. Li, W. Hu, Z. Zhang, M. Zhu, and J. Cheng. Visual tracking via incremental log-euclidean riemannian subspace learning. In CVPR, 2008.
15. X. Li, C. Shen, Q. Shi, A. Dick, and A. van den Hengel. Non-sparse linear representations for visual tracking with online reservoir metric learning. In CVPR, 2012.
16. P. K. Mallapragada, R. Jin, A. K. Jain, and Y. Liu. Semiboost: Boosting for semi-supervised learning. Trans. on PAMI, 31:2000-2014, 2009.
17. X. Mei and H. Ling. Robust visual tracking using 1 minimization. In ICCV, 2009.
18. X. Mei, H. Ling, Y. Wu, E. Blasch, and L. Bai. Minimum error bounded efficient 1 tracker with occlusion detection. In CVPR, 2011.
19. F. Porikli, O. Tuzel, and P. Meer. Covariance tracking using model update based on lie algebra. In CVPR, 2006.
20. C. Rosenberg, M. Hebert, and H. Schneiderman. Semi-supervised self-training of object detection models. In Workshop on Applications of Computer Vision, 2005.
21. D. A. Ross, J. Lim, R. Lin, and M. Yang. Incremental learning for robust visual tracking. Int. J. Comp. Vis., 77(1):125-141, 2008.
22. M. Sugiyama. Dimensionality reduction of multimodal labeled data by local fisher discriminant analysis. Machine Learning Research, 8, 2007.
23. M. A. O. Vasilescu and D. Terzopoulos. Tensor textures: multilinear imagebased rendering. In ACM SIGGRAPH, 2004.
24. Q. Wang, F. Chen, and W. Xu. Tracking by third-order tensor representation. Trans. on SMCB, 41(2):385-396, 2011.
25. J. Wen, X. Gao, X. Li, and D. Tao. Incremental learning of weighted tensor subspace for visual tracking. In Int. Conf. on Sys., Man, and Cyb., 2009.
26. Y.Wu, J. Cheng, J.Wang, and H. Lu. Real-time visual tracking via incremental covariance tensor learning. In ICCV, 2009.
27. S. Yan, D. Xu, S. Lin, T. S. Huang, and S. F. Chang. Element rearrangement for tensor-based subspace learning. In CVPR, 2007.
28. S. Yan, D. Xu, B. Zhang, H. Zhang, Q. Yang, and S. Lin. Graph embedding and extensions: A general framework for dimensionality reduction. Trans. on PAMI, 29:40-51, 2007.
29. J. Ye. Generalized low rank approximations of matrices. Machine Learning, 61:167-191, 2005.
30. J. Ye, R. Janardan, and Q. Li. Two-dimensional linear discriminant analysis. In NIPS, 2004.
31. A. Yilmaz, O. Javed, and M. Shah. Object tracking: A survey. ACM Computing Surveys, 38(4):13, 2006.
32. L. Zelnik-Manor and P. Perona. Self-tuning spectral clustering. In NIPS, 2005.
33. T. Zhang, B. Ghanem, S. Liu, and N. Ahuja. Low-rank sparse learning for robust visual tracking. In ECCV, 2012.
34. T. Zhang, B. Ghanem, S. Liu, and N. Ahuja. Robust visual tracking via multitask sparse learning. In CVPR, 2012.
35. X. Zhang, W. Hu, S. Maybank, and X. Li. Graph based discriminative learning for robust and efficient object tracking. In ICCV, 2007.