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Automatic detection of dangerous motion behavior in human crowds

 
: Krausz, Barbara; Bauckhage, Christian

:
Preprint urn:nbn:de:0011-n-1890201 (1.8 MByte PDF)
MD5 Fingerprint: 7bea86b6eeae059b6d6166f1e6c35565
© 2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Created on: 5.4.2012


Institute of Electrical and Electronics Engineers -IEEE-:
AVSS 2011, IEEE 8th International Conference on Advanced Video and Signal-based Surveillance : 30. August 2011 - 02. September 2011, Klagenfurt University
New York, NY: IEEE, 2011
ISBN: 978-1-4577-0844-2
ISBN: 1-4577-0844-2
ISBN: 978-1-4577-0843-5
ISBN: 978-1-4577-0845-9
pp.224-229
International Conference on Advanced Video and Signal-based Surveillance (AVSS) <8, 2011, Klagenfurt>
English
Conference Paper, Electronic Publication
Fraunhofer IAIS ()
video surveillance; crowd monitoring; congestion; shock wave; mass behavior

Abstract
Tragically, mass gatherings such as music festivals, sports events or pilgrimage quite often end in terrible crowd disasters with many victims. In the past, research focused on developing physical models that model human behavior in order to simulate pedestrian flows and to identify potentially hazardous locations. However, no automatic systems for detection of dangerous motion behavior in crowds exist. In this paper, we present an automatic system for the detection and early warning of dangerous situations during mass events. It is based on optical flow computations and detects patterns of crowd motion that are characteristic for hazardous congestions. By applying an online change-point detection algorithm, the system is capable of identifying changes in pedestrian flow and thus alarms security personnel to take necessary actions.

: http://publica.fraunhofer.de/documents/N-189020.html