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CamInSens - demonstration of a distributed smart camera system for in-situ threat detection

: Grenz, Carsten; Jänen, Uwe; Hähner, Jörg; Kuntzsch, Colin; Menze, Moritz; d'Angelo, David; Bogen, Manfred; Monari, Eduardo

Preprint urn:nbn:de:0011-n-2250801 (10 MByte PDF)
MD5 Fingerprint: d5acb2c15921e23685be7d92172582c7
© ACM 2012 This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution.
Erstellt am: 16.1.2013

Institute of Electrical and Electronics Engineers -IEEE-; Association for Computing Machinery -ACM-:
ICDSC 2012, 6th ACM/IEEE International Conference on Distributed Smart Cameras : Oct 30 - Nov 2, 2012, Hong Kong
New York: ACM, 2012
ISBN: 978-1-4503-1772-6
2 S.
International Conference on Distributed Smart Cameras (ICDSC) <6, 2012, Hong Kong>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IAIS ()
Fraunhofer IOSB ()
distributed resource management; multi-camera multi-person tracking; self-learning classification of spatio-temporal trajectory data; visualization and interaction with self-organizing smart camera systems; classification algorithm; distributed smart cameras; multi-person tracking; self-organizing system; threat detection; trajectory analysis; video surveillance systems; visual analytics

The CamInSens system is a next-generation selforganizing video surveillance system that combines research being done in the fields of person-tracking, trajectory analysis, visual analytics, and self-organizing system management algorithms. Its purpose is the online threat detection by analysing anomalies in persons trajectories. Therefore, robust multicamera multi-person tracking is combined with a flexible analysis module, which uses online learning classification algorithms as well as user-generated filters to process the persons trajectories in the surveillance space.