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Estimation of crowd behaviour using sensor networks and sensor fusion
FOI Swedish Defence Research Agency.
FOI Swedish Defence Research Agency.
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering. FOI Swedish Defence Research Agency.ORCID iD: 0000-0002-6763-5487
2009 (English)Conference paper (Refereed)
Abstract [en]

Commonly, surveillance operators are today monitoring a large number of CCTV screens, trying to solve the complex cognitive tasks of analyzing crowd behavior and detecting threats and other abnormal behavior. Information overload is a rule rather than an exception. Moreover, CCTV footage lacks important indicators revealing certain threats, and can also in other respects be complemented by data from other sensors. This article presents an approach to automatically interpret sensor data and estimate behaviors of groups of people in order to provide the operator with relevant warnings. We use data from distributed heterogeneous sensors (visual cameras and a thermal infrared camera), and process the sensor data using detection algorithms. The extracted features are fed into a hidden Markov model in order to model normal behavior and detect deviations. We also discuss the use of radars for weapon detection.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2009. 396-403 p.
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:liu:diva-120557OAI: oai:DiVA.org:liu-120557DiVA: diva2:846261
Conference
12th International Conference on Information Fusion (FUSION)
Available from: 2015-08-14 Created: 2015-08-14 Last updated: 2015-09-07

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Ahlberg, Jörgen
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Computer VisionFaculty of Science & Engineering
Computer Vision and Robotics (Autonomous Systems)

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ReferencesLink to record
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