NDLI: Automatic congestion detection system for underground platforms

Content Provider	IEEE Xplore Digital Library
Author	Lo, B.P.L. Velastin, S.A.
Copyright Year	2001
Description	Author affiliation: Dept. of Electron. Eng., King's Coll., London, UK (Lo, B.P.L.)
Abstract	An automatic monitoring system is proposed in this paper for detecting overcrowding conditions in the platforms of underground train services. Whenever overcrowding is detected, the system will notify the station operators to take appropriate actions to prevent accidents, such as people falling off or being pushed onto the tracks. The system is designed to use existing closed circuit television (CCTV) cameras for acquiring images of the platforms. In order to focus on the passengers on the platform, background subtraction and update techniques are used. In addition, due to the high variation of brightness on the platforms, a variance filter is introduced to optimize the removal of background pixels. A multi-layer feed forward neural network was developed for classifying the levels of congestion. The system was tested with recorded video from the London Bridge station, and the testing results were shown to be accurate in identifying overcrowding conditions for the unique platform environment.
Starting Page	158
Ending Page	161
File Size	404503
Page Count	4
File Format	PDF
ISBN	9628576623
DOI	10.1109/ISIMP.2001.925356
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-05-04
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Condition monitoring System testing TV Filters Computerized monitoring Circuits Brightness Cameras Feeds Accidents
Content Type	Text
Resource Type	Article

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