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
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;
Conference_Titel :
Information Science and Engineering (ISISE), 2012 International Symposium on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4673-5680-0
DOI :
10.1109/ISISE.2012.117
