• DocumentCode
    1906407
  • Title

    Acceptance of automatic situation assessment in surveillance systems

  • Author

    Fischer, Yvonne ; Beyerer, Jürgen

  • Author_Institution
    Vision & Fusion Lab., Karlsruhe Inst. of Technol. (KIT), Karlsruhe, Germany
  • fYear
    2012
  • fDate
    6-8 March 2012
  • Firstpage
    324
  • Lastpage
    331
  • Abstract
    In today´s surveillance systems, there is a need for enhancing the situation awareness of an operator. Supporting the situation assessment process can be done by extending the system with a module for automatic interpretation of the observed environment. In this article we introduce a consistent terminology for the domain of intelligent surveillance systems. We clarify the separation of the real world and the world model, which is used for the internal representation in the system. For the definition of an automatic situation assessment module, we make use of an existing conceptual framework. We will further introduce a concept for an internal representation of situations of interest and show how the existence of such situations can be inferred from sensor observations. Based on these considerations, an automatic situation assessment module for a maritime surveillance system was developed. The module was evaluated with a small user group and the results show that such an automatic support reduces the workload of the user and is highly accepted.
  • Keywords
    belief networks; military computing; probability; surveillance; Bayesian network; automatic situation assessment; conditional probability; intelligent surveillance system; maritime surveillance system; sensor observation; situation internal representation; Bayesian methods; Character recognition; Data models; Hidden Markov models; Joints; Streaming media; Surveillance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cognitive Methods in Situation Awareness and Decision Support (CogSIMA), 2012 IEEE International Multi-Disciplinary Conference on
  • Conference_Location
    New Orleans, LA
  • Print_ISBN
    978-1-4673-0343-9
  • Type

    conf

  • DOI
    10.1109/CogSIMA.2012.6188404
  • Filename
    6188404