Real-Time Tracking with Online Constrained Compressive Learning

Author:

GUO Bo1,LIU Juan1

Affiliation:

1. School of Computer, Wuhan University

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Artificial Intelligence,Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Hardware and Architecture,Software

Reference15 articles.

1. [1] S. Avidan, “Ensemble tracking,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.494-501, 2005.

2. [2] H. Grabner, C. Leistner, and H. Bischof, “Semi-supervised on-line boosting for robust tracking,” ECCV, pp.234-247, 2008.

3. [3] B. Babenko, M.H. Yang, and S. Belongie, “Robust Object Tracking with Online Multiple Instance Learning,” IEEE Trans. Pattern Anal. Mach. Intell., vol.33, no.8, pp.1619-1632, 2011.

4. [4] K. Zhang, L. Zhang, and M. Yang, “Real-time compressive tracking,” ECCV, pp.864-867, 2012.

5. [5] Z. Kalal, K. Mikolajczyk, and J. Matas, “Tracking-Learning-Detection.,” IEEE Trans. Pattern Anal. Mach. Intell., vol.6, no.1, pp.1-14, 2011.

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Combining Color Features for Real-Time Correlation Tracking;IEICE Transactions on Information and Systems;2017

2. Feature Adaptive Correlation Tracking;IEICE Transactions on Information and Systems;2017

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