Automatic congestion detection system for underground platforms

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...

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Bibliographic Details
Published inProceedings of 2001 International Symposium on Intelligent Multimedia, Video and Speech Processing. ISIMP 2001 (IEEE Cat. No.01EX489) pp. 158 - 161
Main Authors Lo, B.P.L., Velastin, S.A.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2001
Subjects
Accidents
Brightness
Cameras
Circuits
Computerized monitoring
Condition monitoring
Feeds
Filters
System testing
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Summary: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.
ISBN:9789628576623
9628576623
DOI:10.1109/ISIMP.2001.925356