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Adaptive Background Generation for Video Object Segmentation

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Advances in Visual Computing (ISVC 2006)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4291))

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Abstract

In this paper, we present a novel method for generating background that adopts frame difference and a median filter to sensitive areas where illumination changes occur. The proposed method also uses fewer frames than the existing methods. Background generation is widely used as a preprocessing for video-based tracking, surveillance, and object detection. The proposed background generation method utilizes differences and motion changes between two consecutive frames to cope with the changes of illumination in an image sequence. It also utilizes a median filter to adaptively generate a robust background. The proposed method enables more efficient background reconstruction with fewer frames than existing methods use.

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Author information

Authors and Affiliations

  1. Image Processing and Intelligent Systems Laboratory, Department of Image Engineering, Graduate School of Advanced Imaging Science, Multimedia, and Film, Chung-Ang University, 221 Huksuk-dong, Tongjak-Ku, Seoul, 156-756, Korea

    Taekyung Kim & Joonki Paik

Authors
  1. Taekyung Kim
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  2. Joonki Paik
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Nevada, Reno, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, CA, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, NV, USA

    Darko Koracin

  5. Digital Image Research Center, Kingston University, London, UK

    Paolo Remagnino

  6. Intel, 95052, Santa Clara, CA, USA

    Ara Nefian

  7. University of California, 430, Computer Science Building, 92697-3425, Irvine, CA, USA

    Gopi Meenakshisundaram

  8. Institute for Data Analysis and Visualization, P.O. Box

    Valerio Pascucci

  9. Department of Computer Science and Engineering, Czech Technical University in Prague, Czech

    Jiri Zara

  10. Rockwell Scientific, 1049 Camino Dos Rios, 91360, Thousand Oaks, CA, USA

    Jose Molineros

  11. Computer Graphics Group, Bielefeld University, D-33501, Bielefeld, Germany

    Holger Theisel

  12. Hewlett Packard Labs, Palo Alto, CA, USA

    Tom Malzbender

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© 2006 Springer-Verlag Berlin Heidelberg

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Kim, T., Paik, J. (2006). Adaptive Background Generation for Video Object Segmentation. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2006. Lecture Notes in Computer Science, vol 4291. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11919476_87

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  • DOI: https://doi.org/10.1007/11919476_87

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-48628-2

  • Online ISBN: 978-3-540-48631-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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