• DocumentCode
    693668
  • Title

    A system of abnormal behaviour detection in aerial surveillance

  • Author

    Walha, Ahlem ; Wali, Ali ; Alimi, Adel M.

  • Author_Institution
    REGIM: Res. Groups on Intell. Machines, Univ. of Sfax, Sfax, Tunisia
  • fYear
    2013
  • fDate
    4-6 Dec. 2013
  • Firstpage
    102
  • Lastpage
    107
  • Abstract
    Aerial Video-Surveillance systems are being more and more used in security applications. The analysis and detection of abnormal behaviours in a aerial sequence has progressively drawn the attention in the field of public area security, 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 an intelligent video-surveillance framework for abnormal behaviour detection in aerial video surveillance. This framework is attended to be able to achieve real-time alarming, in public areas. This architecture takes into consideration four main challenges: behaviour understanding in public area, aerial video challenges, unstable video and contextual-based adaptability to recognize the active context of the scene.
  • Keywords
    alarm systems; object detection; video surveillance; abnormal behaviour detection; active scene context recognition; aerial sequence; aerial video-surveillance systems; behaviour understanding; contextual-based adaptability; intelligent video-surveillance framework; public area security; real-time alarm; Algorithm design and analysis; Context; Image recognition; Noise; Object detection; Streaming media; Tracking; Pattern recognition; aerial video surveillance; public area; video stabilisation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Assurance and Security (IAS), 2013 9th International Conference on
  • Conference_Location
    Gammarth
  • Print_ISBN
    978-1-4799-2989-4
  • Type

    conf

  • DOI
    10.1109/ISIAS.2013.6947741
  • Filename
    6947741