DocumentCode :
254721
Title :
A Train Station Surveillance System: Challenges and Solutions
Author :
Ozer, Burak ; Wolf, Michael
fYear :
2014
fDate :
23-28 June 2014
Firstpage :
652
Lastpage :
657
Abstract :
In this paper, we describe our multi-year development effort to create a smart-camera surveillance system for use in train stations. We address the problem of activity analysis in very crowded areas and offer solutions to the detection/tracking problems in one of the most crowded environments. The smart camera system is installed in several train stations around Tokyo, Japan and is currently deployed analyzing crowd movement and individual gestures of the passengers in the stations. The paper summarizes the technical problems we faced during our research /development stages as well as during system deployment. The hierarchical smart camera system, which can detect the overall crowd movement in the higher level and individual activities in the lower level, is developed by Verificon Corp., a Princeton University startup company. We developed smart camera algorithms and spent several years commercializing the technology in a joint project with Yokogawa Electric. A railway company was the lead customer on this project. Verificon system passed several rounds of testing, running for several months on live data in several Tokyo train stations and was deployed by the railway company. This project has led to several extensions of the original technology.
Keywords :
intelligent sensors; rail traffic; railways; traffic engineering computing; video signal processing; video surveillance; Japan; Princeton University startup company; Tokyo; Verificon Corp; Yokogawa Electric; activity analysis; crowd movement detection; hierarchical smart camera system; smart-camera surveillance system; train station surveillance system; Algorithm design and analysis; Cameras; Computational modeling; Lighting; Smart cameras; Tracking; Training; gesture recognitionin; surveillance; tracking;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition Workshops (CVPRW), 2014 IEEE Conference on
Conference_Location :
Columbus, OH
Type :
conf
DOI :
10.1109/CVPRW.2014.99
Filename :
6910049
Link To Document :
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