Towards feature-based situation assessment for airport apron video surveillance

  • Authors:
  • Ralf Dragon;Michele Fenzi;Wolf Siberski;Bodo Rosenhahn;Jörn Ostermann

  • Affiliations:
  • Institut für Informationsverarbeitung, Germany;Institut für Informationsverarbeitung, Germany;L3S, Leibniz Universität Hannover, Germany;Institut für Informationsverarbeitung, Germany;Institut für Informationsverarbeitung, Germany

  • Venue:
  • Proceedings of the 15th international conference on Theoretical Foundations of Computer Vision: outdoor and large-scale real-world scene analysis
  • Year:
  • 2011

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Abstract

We present a feature-based surveillance pipeline which, in contrast to traditional image-based methods, allows to learn a detailed description of the observed background as well as of foreground objects. The pipeline consists of motion segmentation of feature trajectories and subsequent tracking-by-recognition with updates. Furthermore, 3D object representations are learned in order to extract the 3D object pose of a later object recognition. Finally, we show how such sufficiently reliable information is inputted into a reasoning system comparing actual and nominal condition of an airport apron. By this, automatic situation assessment becomes possible in a manageable and reliable way.