NDLI: A MRF-based approach for real-time subway monitoring

Content Provider	IEEE Xplore Digital Library
Author	Paragios, N. Ramesh, V.
Copyright Year	2001
Description	Author affiliation: Siemens Corp. Res. Inc., Princeton, NJ, USA (Paragios, N.; Ramesh, V.)
Abstract	There has been an increase in the use of video surveillance and monitoring in public areas to improve safety and security. Change detection and crowding/congestion density estimation are two sub-tasks in a subway monitoring system. We propose a method that decomposes this problem into two steps. The first step consists of a change detection algorithm that distinguishes the background from the foreground. This is done using a discontinuity preserving MRF-based approach where the information from different sources (background subtraction, intensity modeling) is combined with spatial constraints to provide a smooth motion detection map. Then, the obtained change detection map is combined with a geometry module that performs a soft auto-calibration to estimate a measure of congestion of the observed area (platform). Extensive experimental results in a metro station of a metropolitan city demonstrates the performance and the potential of our method.
Sponsorship	IEEE Comput. Soc. Tech. Committee on Pattern Analysis & Machine Intelligence
File Size	954350
File Format	PDF
ISBN	0769512720
ISSN	10636919
DOI	10.1109/CVPR.2001.990644
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-12-08
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Monitoring Video surveillance Safety Security Detection algorithms Motion detection Geometry Performance evaluation Area measurement Cities and towns
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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