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Markovian Framework for Foreground-Background-Shadow Separation of Real World Video Scenes

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Computer Vision – ACCV 2006 (ACCV 2006)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3851))

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Abstract

In this paper we give a new model for foreground-back-ground-shadow separation. Our method extracts the faithful silhouettes of foreground objects even if they have partly background like colors and shadows are observable on the image. It does not need any a priori information about the shapes of the objects, it assumes only they are not point-wise. The method exploits temporal statistics to characterize the background and shadow, and spatial statistics for the foreground. A Markov Random Field model is used to enhance the accuracy of the separation. We validated our method on outdoor and indoor video sequences captured by the surveillance system of the university campus, and we also tested it on well-known benchmark videos.

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References

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Author information

Authors and Affiliations

  1. Department of Information Technology, Pázmány Péter Catholic University, H-1083, Budapest, Práter utca 50/A, Hungary

    Csaba Benedek

  2. Analogical Computing Laboratory, Computer and Automation Institute, Hungarian Academy of Sciences, H-1111, Budapest, Kende u. 13-17, Hungary

    Tamás Szirányi

Authors
  1. Csaba Benedek
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  2. Tamás Szirányi
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Editor information

Editors and Affiliations

  1. International Institute of Information Technology, Center for Visual Information Technology, Hyderabad, India

    P. J. Narayanan

  2. Department of Computer Science, Columbia University, 500 West 120th Street, 10027, New York, NY, USA

    Shree K. Nayar

  3. Microsoft Research Asia, Beijing, P.R. China

    Heung-Yeung Shum

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© 2006 Springer-Verlag Berlin Heidelberg

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Benedek, C., Szirányi, T. (2006). Markovian Framework for Foreground-Background-Shadow Separation of Real World Video Scenes. In: Narayanan, P.J., Nayar, S.K., Shum, HY. (eds) Computer Vision – ACCV 2006. ACCV 2006. Lecture Notes in Computer Science, vol 3851. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11612032_90

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  • DOI: https://doi.org/10.1007/11612032_90

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-31219-2

  • Online ISBN: 978-3-540-32433-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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