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Region Covariance Matrices for Object Tracking in Quasi-Monte Carlo Filter

  • Conference paper
Signal Processing and Multimedia (MulGraB 2010, SIP 2010)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 123))

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Abstract

Region covariance matrices (RCMs), categorized as a matrix-form feature in a low dimension, fuse multiple different image features which might be correlated. The region covariance matrices-based trackers are robust and versatile with a modest computational cost. In this paper, under the Bayesian inference framework, a region covariance matrices-based quasi-Monte Carlo filter tracker is proposed. The RCMs are used to model target appearances. The dissimilarity metric of the RCMs are measured on Riemannian manifolds. Based on the current object location and the prior knowledge, the possible locations of the object candidates in the next frame are predicted by combine both sequential quasi-Monte Carlo (SQMC) and a given importance sampling (IS) techniques. Experiments performed on different type of image sequence show our approach is robust and effective.

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Author information

Authors and Affiliations

  1. College of Computer and Information Engineering, Hohai University, Nanjing, 210098, China

    Xiaofeng Ding, Lizhong Xu, Xin Wang & Guofang Lv

Authors
  1. Xiaofeng Ding
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  2. Lizhong Xu
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  3. Xin Wang
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  4. Guofang Lv
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Editor information

Editors and Affiliations

  1. Hannam University, Daejeon, South Korea

    Tai-hoon Kim

  2. Indian Statistical Institute, Kolkata, India

    Sankar K. Pal

  3. Department of Computer and Information Science, University of Michigan – Dearborn, 4901 Evergreen Road, 48128, Dearborn, MI, USA

    William I. Grosky

  4. Florida International University, EC 2910, 10555 W. Flagler Street, 33174, Miami, FL, USA

    Niki Pissinou

  5. National Taipei University of Education, No.134, Sec. 2, Heping E. Rd., Da-an District, 106, Taipei City, Taiwan (R.O.C.)

    Timothy K. Shih

  6. University of Warsaw & Infobright Inc., Poland

    Dominik Ślęzak

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© 2010 Springer-Verlag Berlin Heidelberg

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Ding, X., Xu, L., Wang, X., Lv, G. (2010). Region Covariance Matrices for Object Tracking in Quasi-Monte Carlo Filter. In: Kim, Th., Pal, S.K., Grosky, W.I., Pissinou, N., Shih, T.K., Ślęzak, D. (eds) Signal Processing and Multimedia. MulGraB SIP 2010 2010. Communications in Computer and Information Science, vol 123. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17641-8_13

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  • DOI: https://doi.org/10.1007/978-3-642-17641-8_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17640-1

  • Online ISBN: 978-3-642-17641-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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