Fast compressive tracking combined with Kalman filter-Reference-Cited by-同舟云学术

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Fast compressive tracking combined with Kalman filter

Published:2019-04-17 Issue:16 Volume:78 Page:22463-22477
ISSN:1380-7501
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Chen Jinguang,Li Xiaoxing,Wang Mingming,Ma Lili,Xu Bugao

Funder

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Link

http://link.springer.com/content/pdf/10.1007/s11042-019-7514-7.pdf

Reference36 articles.

1. Babenko B, Yang MH, Belongie S (2011) Robust object tracking with online multiple instance learning. IEEE Trans Pattern Anal Mach Intell 33(8):1619–1632. https://doi.org/10.1109/TPAMI.2010.226

2. Bao C, Wu Y, Ling H et al. (2012) Real time robust L1 tracker using accelerated proximal gradient approach. IEEE Conference on Computer Vision and Pattern Recognition, Providence, RI, USA: 1830–1837. doi: https://doi.org/10.1109/CVPR.2012.6247881

3. Bolme SD, Beveridge RJ, Draper AB, Lui MY (2010) Visual object tracking using adaptive correlation filters. IEEE Conf Comput Vision Pattern Recognition, San Francisco, CA, USA: 2544–2550. doi: https://doi.org/10.1109/CVPR.2010.5539960

4. Comaniciu D, Ramesh V, Meer P (2003) Kernel-based object tracking. IEEE Trans Pattern Anal Mach Intell 25(5):564–577. https://doi.org/10.1109/TPAMI.2003.1195991

5. Danelljan M, Häger G, Khan SF, Felsberg M (2017) Discriminative scale space tracking. IEEE Trans Pattern Anal Mach Intell 39(8):1561–1575. https://doi.org/10.1109/TPAMI.2016.2609928

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