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Proceedings Paper

Application-driven merging and analysis of person trajectories for distributed smart camera networks
Author(s): Jürgen Metzler; Eduardo Monari; Colin Kuntzsch
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Paper Abstract

Tracking of persons and analysis of their trajectories are important tasks of surveillance systems as they support the monitoring personnel. However, this trend is accompanied by an increasing demand on smarter camera networks carrying out surveillance tasks autonomously. Thus, there is a higher system complexity so that requirements on the video analysis algorithms are increasing as well. In this paper, we present a system concept and application for anonymously gathering, processing and analysis of trajectories in distributed smart camera networks. It allows a multitude of analysis techniques such as inspecting individual properties of the observed movement in real-time. Additionally, the anonymous movement data allows long-term storage and big data analyses for statistical purposes. The system described in this paper has been implemented as prototype system and deployed for proof of concept under real conditions at the entrance hall of the Leibniz University Hannover. It shows an overall stable performance, particularly with respect to significant illumination changes over hours, as well as regarding the reduction of false positives by post processing and trajectory merging performed on top of a panorama based person detection module.

Paper Details

Date Published: 5 March 2014
PDF: 9 pages
Proc. SPIE 9026, Video Surveillance and Transportation Imaging Applications 2014, 90260I (5 March 2014); doi: 10.1117/12.2038964
Show Author Affiliations
Jürgen Metzler, Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung (Germany)
Eduardo Monari, Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung (Germany)
Colin Kuntzsch, Leibniz Univ. Hannover (Germany)


Published in SPIE Proceedings Vol. 9026:
Video Surveillance and Transportation Imaging Applications 2014
Robert P. Loce; Eli Saber; Ned Lecky, Editor(s)

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