• DocumentCode
    7651
  • Title

    Video scene invariant crowd density estimation using geographic information systems

  • Author

    Song Hongquan ; Liu Xuejun ; Lu Guonian ; Zhang Xingguo ; Wang Feng

  • Author_Institution
    State Key Lab. of Cotton Biol., Henan Univ., Kaifeng, China
  • Volume
    11
  • Issue
    11
  • fYear
    2014
  • fDate
    Nov. 2014
  • Firstpage
    80
  • Lastpage
    89
  • Abstract
    Crowd density is an important factor of crowd stability. Previous crowd density estimation methods are highly dependent on the specific video scene. This paper presented a video scene invariant crowd density estimation method using Geographic Information Systems (GIS) to monitor crowd size for large areas. The proposed method mapped crowd images to GIS. Then we can estimate crowd density for each camera in GIS using an estimation model obtained by one camera. Test results show that one model obtained by one camera in GIS can be adaptively applied to other cameras in outdoor video scenes. A real-time monitoring system for crowd size in large areas based on scene invariant model has been successfully used in `Jiangsu Qinhuai Lantern Festival, 2012´. It can provide early warning information and scientific basis for safety and security decision making.
  • Keywords
    geographic information systems; video signal processing; GIS; crowd stability; geographic information systems; outdoor video scenes; real-time monitoring system; video scene invariant crowd density estimation method; Adaptation models; Cameras; Crowdsourcing; Density measurement; Feature extraction; Geographic information systems; Surveillance; GIS; crowd density estimation; video scene invariant; video spatial registration;
  • fLanguage
    English
  • Journal_Title
    Communications, China
  • Publisher
    ieee
  • ISSN
    1673-5447
  • Type

    jour

  • DOI
    10.1109/CC.2014.7004526
  • Filename
    7004526