Sparse representation combined with context information for visual tracking-Reference-Cited by-同舟云学术

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Sparse representation combined with context information for visual tracking

Published:2017-02 Issue: Volume:225 Page:92-102
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Feng Ping,Xu Chunyan,Zhao Zhiqiang,Liu Fang,Yuan Caihong,Wang Tianjiang,Duan Kui

Funder

Natural Science Foundation of China

Huazhong University of Science and Technology

Wuhan Science and Technology Bureau of Hubei Province, China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference54 articles.

1. H. Grabner, M. Grabner, H. Bischof, Real-time tracking via on-line boosting, in: BMVC, vol. 1, no. 5, 2006, p. 6.

2. Incremental learning for robust visual tracking;Ross;Int. J. Comput. Vis.,2008

3. B. Babenko, M.-H. Yang, S. Belongie, Visual tracking with online multiple instance learning, in: CVPR, 2009, pp. 983–990.

4. J. Kwon, K.M. Lee, Visual tracking decomposition, in: CVPR, 2010, pp. 1269–1276.

5. L. Sevilla-Lara, E. Learned-Miller, Distribution fields for tracking, in: CVPR, 2012, pp. 1910–1917

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1. Graph Theory: A Comprehensive Survey about Graph Theory Applications in Computer Science and Social Networks;Inventions;2020-02-20

2. Learning Local Structured Correlation Filters for Visual Tracking via Spatial Joint Regularization;IEEE Access;2019

3. Real-Time Sparse Visual Tracking Using Circulant Reverse Lasso Model;IEICE Transactions on Information and Systems;2019-01-01

4. Visual tracking via context-aware local sparse appearance model;Journal of Visual Communication and Image Representation;2018-10

5. A deep features based generative model for visual tracking;Neurocomputing;2018-09

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