%Aigaion2 BibTeX export van HES SO Valais Publications
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@INPROCEEDINGS{,
        author = {Charara, Nour and Jarkass, Iman and Maria, Sokhn and Mugellini, Elena and Abou Khaled, Omar},
      keywords = {Behavior recognition, Crowded scene, data fusion, Pattern Recognition, Video-surveillance},
         month = aug,
         title = {ADABeV: Automatic Detection of Abnormal Behavior in Video-surveillance},
          year = {2012},
      location = {Oslo, Norway},
  organization = {International Conference on Image, Signal and Vision Computing},
      abstract = {Intelligent Video-Surveillance (IVS) systems are
being more and more popular in security applications. The analysis
and recognition of abnormal behaviours in a video sequence has
gradually drawn the attention in the field of IVS, since it allows
filtering out a large number of useless information, which guarantees
the high efficiency in the security protection, and save a lot of human
and material resources. We present in this paper ADABeV, an
intelligent video-surveillance framework for event recognition in
crowded scene to detect the abnormal human behaviour. This
framework is attended to be able to achieve real-time alarming,
reducing the lags in traditional monitoring systems. This architecture
proposal addresses four main challenges: behaviour understanding in
crowded scenes, hard lighting conditions, multiple input kinds of
sensors and contextual-based adaptability to recognize the active
context of the scene.}
}