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
Link To Document :
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