• DocumentCode
    1911047
  • Title

    Research on Moving Object Detection Method of High-Speed Railway Transport Hub Video Surveillance

  • Author

    Xie Zhengyu ; Jia Limin ; Qin Yong ; Wang Li

  • Author_Institution
    State Key Lab. of Rail Traffic Control & Safety, Beijing Jiaotong Univ., Beijing, China
  • fYear
    2012
  • fDate
    14-16 Dec. 2012
  • Firstpage
    315
  • Lastpage
    318
  • Abstract
    Detect moving objects from a video sequence is a fundamental and critical task in many computer vision application. For security forewarning demand of the high-speed railway transport hub video surveillance system, we need a stable, fast and accurate moving object detection method to promptly find the congestion of passenger flow and other dangerous in hub. Through the comparative study on moving object detection, we select average background model to build background and gray area division to improve the processing speed of background modeling. Experiment result shows our method is suitable for high-speed railway transport hub video surveillance.
  • Keywords
    computer vision; image sequences; motion estimation; object detection; railway engineering; railway safety; rapid transit systems; transportation; video surveillance; average background model selection; background area division; background modeling processing speed improvement; computer vision application; gray area division; high-speed railway transport hub video surveillance; hub danger detection; moving object detection method; passenger flow congestion detection; security forewarning demand; video sequence; Background subtraction; High-speed railway transport hub; Moving object detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Engineering (ISISE), 2012 International Symposium on
  • Conference_Location
    Shanghai
  • ISSN
    2160-1283
  • Print_ISBN
    978-1-4673-5680-0
  • Type

    conf

  • DOI
    10.1109/ISISE.2012.117
  • Filename
    6495355