Robust Visual Tracking Based on Convolutional Features with Illumination and Occlusion Handing-Reference-Cited by-同舟云学术

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Robust Visual Tracking Based on Convolutional Features with Illumination and Occlusion Handing

Published:2018-01 Issue:1 Volume:33 Page:223-236
ISSN:1000-9000
Container-title:Journal of Computer Science and Technology
language:en
Short-container-title:J. Comput. Sci. Technol.

Author:

Li Kang,He Fa-Zhi,Yu Hai-Ping

Publisher

Springer Science and Business Media LLC

Subject

Computational Theory and Mathematics,Computer Science Applications,Hardware and Architecture,Theoretical Computer Science,Software

Link

http://link.springer.com/article/10.1007/s11390-017-1764-5/fulltext.html

Reference43 articles.

1. Wang N Y, Shi J P, Yeung D Y, Jia J Y. Understanding and diagnosing visual tracking systems. In Proc. IEEE Int. Conf. Computer Vision, December 2015, pp.3101-3109.

2. Zhang X Q, Hu W M, Bao H J, Maybank S. Robust head tracking based on multiple cues fusion in the kernel-Bayesian framework. IEEE Trans. Circuits and Systems for Video Technology, 2013, 23(7): 1197-1208.

3. Zhang X Q, Hu W M, Xie N H, Bao H J, Maybank S. A robust tracking system for low frame rate video. International Journal of Computer Vision, 2015, 115(3): 279-304.

4. Zhang X Q, Hu W M, Qu W, Maybank S. Multiple object tracking via species-based particle swarm optimization. IEEE Trans. Circuits and Systems for Video Technology, 2010, 20(11): 1590-1602.

5. Sun J, He F Z, Chen Y L, Chen X. A multiple template approach for robust tracking of fast motion target. Applied Mathematics-A Journal of Chinese Universities, 2016, 31(2): 177-197.

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