• DocumentCode
    1688923
  • Title

    An Ontology for Event Detection and its Application in Surveillance Video

  • Author

    SanMiguel, Juan Carlos ; Martínez, José M. ; García, Álvaro

  • Author_Institution
    Video Process. & Understanding Lab., Univ. Autonoma de Madrid, Madrid, Spain
  • fYear
    2009
  • Firstpage
    220
  • Lastpage
    225
  • Abstract
    In this paper, we propose an ontology for representing the prior knowledge related to video event analysis. It is composed of two types of knowledge related to the application domain and the analysis system. Domain knowledge involves all the high level semantic concepts in the context of each examined domain (objects, events, context...) whilst system knowledge involves the capabilities of the analysis system (algorithms, reactions to events...). The proposed ontology has been structured in two parts: the basic ontology (composed of the basic concepts and their specializations) and the domain-specific extensions. Additionally, a video analysis framework based on the proposed ontology is defined for the analysis of different application domains showing the potential use of the proposed ontology. In order to show the real applicability of the proposed ontology, it is specialized for the underground video-surveillance domain showing some results that demonstrate the usability and effectiveness of the proposed ontology.
  • Keywords
    knowledge representation; object detection; ontologies (artificial intelligence); video surveillance; event detection; knowledge representation; ontology; underground video-surveillance domain; video event analysis; Algorithm design and analysis; Event detection; Knowledge representation; Layout; Logic; Object detection; Ontologies; Proposals; Resource description framework; 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.2009.28
  • Filename
    5279823