• DocumentCode
    160530
  • Title

    Automatic detection of entry into a restricted area

  • Author

    Sivagurunathan, S. ; Piratla, Aditya ; Surendran, Jayalakshmi ; Das, Mangal

  • Author_Institution
    Global R& D Crompton Greaves Ltd. Mumbai, Mumbai, India
  • fYear
    2014
  • fDate
    11-13 July 2014
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Detecting people and objects entering and exiting a region of interest is an important problem in the area of video surveillance and is typically called virtual fence detection or trip-zone detection. This work proposes two methods to address this problem. The former method deals with cases where a person or object is crossing a horizontal virtual fence while the person or object is moving in a horizontal direction whereas the latter deals with crossing of virtual fence while the person or object is moving in vertical direction. In the first method, crossing of fence by objects as well as persons is detected through simple temporal differencing based motion detection. To detect objects climbing up or down a fence, a spatio-temporal method is proposed. The proposed methods are evaluated under various real life scenarios and results demonstrate the efficiency of the proposed model as well as the real time performance.
  • Keywords
    image motion analysis; object detection; video signal processing; video surveillance; automatic entry detection; horizontal direction; simple temporal differencing based motion detection; spatio-temporal method; trip-zone detection; vertical direction; video surveillance; virtual fence detection; Cameras; Computer vision; Motion detection; Real-time systems; Sensitivity; Streaming media; Surveillance; False Positives; Moments; ONVIF; Virtual Fence;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computing, Communication and Networking Technologies (ICCCNT), 2014 International Conference on
  • Conference_Location
    Hefei
  • Print_ISBN
    978-1-4799-2695-4
  • Type

    conf

  • DOI
    10.1109/ICCCNT.2014.6963126
  • Filename
    6963126