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Robust Object Tracking Based on Uncertainty Factorization Subspace Constraints Optical Flow

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Computational Intelligence and Security (CIS 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3802))

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Abstract

The traditional methods of optical flow estimation have some problems, such as huge computation cost for the inverse of time-varying Hessian matrix, aperture phenomena for the points with 1D or little texture and drift phenomena with long sequences. A novel nonrigid object tracking algorithm based on inverse component uncertainty factorization subspace constraints optical flow is proposed in this paper, which resolves the above problems and achieves fast, robust and precise tracking. The idea of inverse Component is implemented in each recursive estimation procedure to make the algorithm fast. Uncertainty factorization is used to transform the optimization problem from a hyper-ellipse space to a hyper-sphere space. SVD is correspondingly performed to involve the subspace constraints. The proposed algorithm has been evaluated by both the standard test sequence and the consumer USB camera recorded sequence. The potential applications vary from articulated automation to structure from motion.

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Author information

Authors and Affiliations

  1. College of Computer, Northwestern Polytechnical University, Xi’an, 710072, China

    Yunshu Hou, Yanning Zhang & Rongchun Zhao

Authors
  1. Yunshu Hou
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  2. Yanning Zhang
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  3. Rongchun Zhao
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Editor information

Editors and Affiliations

  1. Microelectronic Instiute, Xidian University, 710071, Xi’an, China

    Yue Hao

  2. Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong

    Jiming Liu

  3. School of Computer Science and Technology, Xidian University, Xi’an, China

    Yu-Ping Wang

  4. Department of Computer Science, Hong Kong Baptist University, Hong Kong,  

    Yiu-ming Cheung

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

  6. Life Science Research Center, School of Electronic Engineering, Xidian University, 710071, Xi’an, Shaanxi, China

    Licheng Jiao

  7. Key Laboratory of Computer Networks and Information Security(Ministry of Education), Xidian University, 710071, Xi’an, China

    Jianfeng Ma

  8. National Laboratory of Antennas and Microwave Technology, Xidian University, 710071, Xi’an, Shanxi, P.R. China

    Yong-Chang Jiao

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© 2005 Springer-Verlag Berlin Heidelberg

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Hou, Y., Zhang, Y., Zhao, R. (2005). Robust Object Tracking Based on Uncertainty Factorization Subspace Constraints Optical Flow. In: Hao, Y., et al. Computational Intelligence and Security. CIS 2005. Lecture Notes in Computer Science(), vol 3802. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11596981_128

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  • DOI: https://doi.org/10.1007/11596981_128

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30819-5

  • Online ISBN: 978-3-540-31598-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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