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Robust Real-Time Tracking for Visual Surveillance

EURASIP Journal on Advances in Signal Processing volume 2007, Article number: 096568 (2006) Cite this article

Abstract

This paper describes a real-time multi-camera surveillance system that can be applied to a range of application domains. This integrated system is designed to observe crowded scenes and has mechanisms to improve tracking of objects that are in close proximity. The four component modules described in this paper are (i) motion detection using a layered background model, (ii) object tracking based on local appearance, (iii) hierarchical object recognition, and (iv) fused multisensor object tracking using multiple features and geometric constraints. This integrated approach to complex scene tracking is validated against a number of representative real-world scenarios to show that robust, real-time analysis can be performed.

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Authors and Affiliations

  1. School of Systems Engineering, Computational Vision Group, The University of Reading, Reading, RG6 6AY, UK

    David Thirde, Mark Borg & James Ferryman

  2. Computer Science Department, Pattern Recognition and Image Processing Group, Vienna University of Technology, Vienna, 1040, Austria

    Josep Aguilera, Horst Wildenauer & Martin Kampel

Authors
  1. David Thirde
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  2. Mark Borg
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  3. Josep Aguilera
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  4. Horst Wildenauer
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  5. James Ferryman
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  6. Martin Kampel
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Corresponding author

Correspondence to David Thirde.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License ( https://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Thirde, D., Borg, M., Aguilera, J. et al. Robust Real-Time Tracking for Visual Surveillance. EURASIP J. Adv. Signal Process. 2007, 096568 (2006). https://doi.org/10.1155/2007/96568

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  • DOI: https://doi.org/10.1155/2007/96568

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