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Visual Tracking Using Iterative Sparse Approximation

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Advances in Neural Networks – ISNN 2011 (ISNN 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6676))

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Abstract

Recent research has advocated the use of sparse representation for tracking objects instead of the conventional histogram object representation models used in popular algorithms. In this paper we propose a new tracker. The core is that the tracking results is iteratively updated by gradually optimizing the sparsity and reconstruction error. The effectiveness of the proposed approach is demonstrated via comparative experiments.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Technology, Tsinghua University, P.R. China

    Huaping Liu & Fuchun Sun

  2. State Key Laboratory of Intelligent Technology and Systems, Beijing, P.R. China

    Huaping Liu & Fuchun Sun

  3. Shijiazhuang Tiedao University, Hebei Province, China

    Meng Gao

Authors
  1. Huaping Liu
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  2. Fuchun Sun
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  3. Meng Gao
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Editor information

Editors and Affiliations

  1. Institute of Automation, Key Laboratory of Complex Systems and Intelligence Science, Chinese Academy of Sciences, 100190, Beijing, China

    Derong Liu

  2. College of Information Science and Engineering, Northeastern University, 110004, Shenyang, Liaoing, China

    Huaguang Zhang

  3. Department of Electrical and Computer Engineering, University of Cyprus, 75 Kallipoleos Avenue, 1678, Nicosia, Cyprus

    Marios Polycarpou

  4. Dipartimento di Elettronica, Politecnico di Milano, Piazza L. da Vinci 32, 20133, Milano, Italy

    Cesare Alippi

  5. Deptartment of Electrical, Computer and Biomedical Engineering, University of Rhode Island, 02881, Kingston, RI, USA

    Haibo He

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© 2011 Springer-Verlag Berlin Heidelberg

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Liu, H., Sun, F., Gao, M. (2011). Visual Tracking Using Iterative Sparse Approximation. In: Liu, D., Zhang, H., Polycarpou, M., Alippi, C., He, H. (eds) Advances in Neural Networks – ISNN 2011. ISNN 2011. Lecture Notes in Computer Science, vol 6676. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21090-7_25

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  • DOI: https://doi.org/10.1007/978-3-642-21090-7_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21089-1

  • Online ISBN: 978-3-642-21090-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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