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Adaptive Model for Foreground Extraction in Adverse Lighting Conditions

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PRICAI 2004: Trends in Artificial Intelligence (PRICAI 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3157))

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Abstract

Background elimination models are widely used in motion tracking systems. Our aim is to develop a system that performs reliably under adverse lighting conditions. In particular, this includes indoor scenes lit partly or entirely by diffuse natural light. We present a modified ”median value” model in which the detection threshold adapts to global changes in illumination. The responses of several models are compared, demonstrating the effectiveness of the new model.

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References

  1. Stauffer, C., Grimson, W.E.L.: Learning patterns of activity using real-time tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence 22, 747–757 (2000)

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  3. Butler, D., Sridharan, S.: V. Michael Bove, J.: Real-time adaptive background segmentation. In: Proceedings International Conference on Acoustics, Speech and Signal Processing, ICASSP 2003 (2003)

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  4. Prati, A., Mikic, I., Cucchiara, R., Trivedi, M.M.: Analysis and detection of shadows in video streams: A comparative evaluation. In: IEEE Computer Vision and Pattern Recognition Conference, Hawaii (2001)

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Author information

Authors and Affiliations

  1. Department of Computing, Curtin University of Technology, GPO Box U1987, Perth, 6845, Western Australia

    Stewart Greenhill, Svetha Venkatesh & Geoff West

Authors
  1. Stewart Greenhill
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  2. Svetha Venkatesh
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  3. Geoff West
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Editor information

Editors and Affiliations

  1. Faculty of Engineering and Information Technology, Centre for Quantum Computation and Intelligent Systems, and Australian ACS National Committee for Artificial Intelligence, University of Technology, Sydney, Australia

    Chengqi Zhang

  2. Department of Computer Science, Auckland University of Technology, 1020, Auckland, New Zealand

    Hans W. Guesgen

  3. Artificial Intelligence Technology Centre, Auckland University of Technology, Auckland, New Zealand

    Wai-Kiang Yeap

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© 2004 Springer-Verlag Berlin Heidelberg

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Greenhill, S., Venkatesh, S., West, G. (2004). Adaptive Model for Foreground Extraction in Adverse Lighting Conditions. In: Zhang, C., W. Guesgen, H., Yeap, WK. (eds) PRICAI 2004: Trends in Artificial Intelligence. PRICAI 2004. Lecture Notes in Computer Science(), vol 3157. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28633-2_85

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  • DOI: https://doi.org/10.1007/978-3-540-28633-2_85

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22817-2

  • Online ISBN: 978-3-540-28633-2

  • eBook Packages: Springer Book Archive

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