• DocumentCode
    1978622
  • Title

    SESRG-InViSS: Image and video data set for human pose, action, activity and behaviour detection

  • Author

    Md Saad, Mohamad Hanif ; Hussain, Amir ; Win Kong ; Yasmin, Farah ; Md Tahir, Nooritawati

  • Author_Institution
    Fac. of Eng. & Built Environ., UKM, Bangi, Malaysia
  • fYear
    2013
  • fDate
    19-20 Aug. 2013
  • Firstpage
    37
  • Lastpage
    42
  • Abstract
    This paper introduces the SESRG-InViSS image and video data set for human pose, action, activity and behaviour detection. The dataset consist of 804 images of human actor in various pose (standing front, standing right, standing left, squatting, sitting etc) and 210 videos of human actor/actors in various action (walking, associating and disassociating with an object, holding objects, dragging objects, entering and leaving the ambient), activities (taking out objects from the ambient, moving objects, swapping objects, surveying the ambient, inspecting objects) and behavior (normal and suspicious behaviour). This dataset was used extensively in the development of SESRG´s InViSS (Intelligent Video Surveillance System), an intelligent integrated system for detection, identification and management of human activities from video surveillance recording and live video surveillance feed.
  • Keywords
    image motion analysis; pose estimation; video signal processing; video surveillance; Intelligent Video Surveillance System; SESRG-InViSS; action detection; behaviour detection; human activities identification; human activities management; human activity detection; human pose detection; image data set; intelligent integrated system; live video surveillance feed; video data set; video surveillance recording; Artificial intelligence; Cameras; Conferences; Educational institutions; Legged locomotion; Surveillance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    System Engineering and Technology (ICSET), 2013 IEEE 3rd International Conference on
  • Conference_Location
    Shah Alam
  • Print_ISBN
    978-1-4799-1028-1
  • Type

    conf

  • DOI
    10.1109/ICSEngT.2013.6650139
  • Filename
    6650139