• DocumentCode
    1688612
  • Title

    Modelling and Managing Domain Context for Automatic Surveillance Systems

  • Author

    Snidaro, Lauro ; Belluz, Massimo ; Foresti, Gian Luca

  • Author_Institution
    Dept. of Math. & Comput. Sci., Univ. of Udine, Udine, Italy
  • fYear
    2009
  • Firstpage
    238
  • Lastpage
    243
  • Abstract
    In this paper we propose an architecture for a surveillance application aimed to the automatic recognition of complex events. The main novelty of this work consists in the design of an effective and viable solution for the actual implementation of a complex automatic surveillance system that explicitly separates signal processing routines from the reasoning modules. We describe our ongoing efforts in the representation of the domain knowledge and in the development of a framework that allows the operator to easily check and update the systempsilas knowledge base. The taxonomical knowledge is expressed through ontologies (OWL), the event classification logic is expressed using a dedicated rule language (Jess), and the implementation is based on the java language.
  • Keywords
    Java; image recognition; ontologies (artificial intelligence); signal processing; video surveillance; automatic recognition; automatic surveillance systems; complex events; dedicated rule language; domain knowledge representation; java language; managing domain context; ontologies; signal processing routines; taxonomical knowledge; Bismuth; Context modeling; Surveillance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Video and Signal Based Surveillance, 2009. AVSS '09. Sixth IEEE International Conference on
  • Conference_Location
    Genova
  • Print_ISBN
    978-1-4244-4755-8
  • Electronic_ISBN
    978-0-7695-3718-4
  • Type

    conf

  • DOI
    10.1109/AVSS.2009.68
  • Filename
    5279810