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Towards Feature-Based Situation Assessment for Airport Apron Video Surveillance

Ralf Dragon, Michele Fenzi, Wolf Siberski, Bodo Rosenhahn, Jörn Ostermann
Theoretic Foundations of Computer Vision: Outdoor and Large-Scale Real-World Scene Analysis
2012

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 ob- ject representations are learned in order to extract the 3D object pose of a later object recognition. Finally, we show how such sufficiently re- liable 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.


Link to publisher's page
@InProceedings{eth_biwi_00960,
  author = {Ralf Dragon and Michele Fenzi and Wolf Siberski and Bodo Rosenhahn and J\"orn Ostermann},
  title = {Towards Feature-Based Situation Assessment for Airport Apron Video Surveillance},
  booktitle = {Theoretic Foundations of Computer Vision: Outdoor and Large-Scale Real-World Scene Analysis},
  year = {2012},
  keywords = {}
}