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Adaptive Estimation of Human Posture Using a Component-Based Model

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Pattern Recognition and Image Analysis (ICAPR 2005)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3687))

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Abstract

To detect a human body and recognize its posture, a component-based approach is less susceptible to changes in posture and lighting conditions. This paper proposes a component-based human-body model that comprises ten components and their flexible links. Each component contains geometrical information, appearance information, and information on the links with other components. The proposed method in this paper uses hierarchical links between components of human body, so that it allows to make coarse-to-fine searches and makes human-body matching more time-efficient. To adaptively estimate the posture in change of posture and illumination, we update the component online every time a new human body is incoming.

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References

  1. Fischler, M.A., Elschlager, R.A.: The representation and matching of pictorial structures. IEEE Tran. on Computers 67, 67–92 (1973)

    Article  Google Scholar 

  2. Felzenszwalb, P.F., Huttenlocher, D.P.: Efficient matching of pictorial structures. In: Proc. of CVPR, pp. 66–73 (2000)

    Google Scholar 

  3. Garcia, C., Tziritas, G.: Face detection using quantized skin color regions merging and wavelet packet analysis. IEEE Tran. on Multimedia 1(3), 264–276 (1999)

    Article  Google Scholar 

  4. Lee, K.-M.: Component-based online learning and its application to face detection. In: Proc. of CGIM, pp. 285–290 (2004)

    Google Scholar 

  5. Holstein, H., Li, B.: Low density feature point matching for articulated pose identification. In: Proc. of BMVC, pp.678–687 (2002)

    Google Scholar 

  6. Mittal, A., Zhao, L., Davis, L.S.: Human body pose estimation using silhouette shape analysis. In: Proc. of International conference on advanced video and signal based surveillance, pp. 263–270 (2003)

    Google Scholar 

  7. Hogg, D.C.: Model-based vision: A Program to see a walking person. Image and Vision Computing 1(1), 5–20 (1983)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer Science, Duksung Women’s University, Seoul, Korea

    Kyoung-Mi Lee

Authors
  1. Kyoung-Mi Lee
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Editor information

Editors and Affiliations

  1. Research School of Infomatics, Loughborough, UK

    Sameer Singh

  2. ATR Lab, Research School of Informatics, University of Loughborough, Loughborough, UK

    Maneesha Singh

  3. IBM Corporation, 1133 Wetchester Avenue, White Plains, 10604, New York, United States

    Chid Apte

  4. Institute of Computer Vision and applied Computer Sciences, IBaI, Germany

    Petra Perner

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© 2005 Springer-Verlag Berlin Heidelberg

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Lee, KM. (2005). Adaptive Estimation of Human Posture Using a Component-Based Model. In: Singh, S., Singh, M., Apte, C., Perner, P. (eds) Pattern Recognition and Image Analysis. ICAPR 2005. Lecture Notes in Computer Science, vol 3687. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11552499_36

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  • DOI: https://doi.org/10.1007/11552499_36

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28833-6

  • Online ISBN: 978-3-540-31999-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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