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Privacy-aware object representation for surveillance systems

 
: Vagts, H.; Bauer, A.

:
Postprint urn:nbn:de:0011-n-1427557 (276 KByte PDF)
MD5 Fingerprint: bca56902ef9114e9fbdf35a4e5bef711
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Created on: 14.10.2010


Institute of Electrical and Electronics Engineers -IEEE-:
Seventh IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2010 : Boston, Aug. 29 -Sept. 1 2010
New York, NY: IEEE, 2010
ISBN: 978-0-7695-4264-5
ISBN: 978-1-4244-8310-5
pp.601-608
International Conference on Advanced Video and Signal Based Surveillance (AVSS) <7, 2010, Boston/Mass.>
English
Conference Paper, Electronic Publication
Fraunhofer IOSB ()

Abstract
Real-time object tracking, feature assessment and classification based on video are an enabling technology for improving situation awareness of human operators as well as for automated recognition of critical situations. To bridge the gap between video signal-processing output and spatio-temporal analysis of object behavior at the semantic level, a generic and sensor-independent object representation is necessary. However, in the case of public and corporate video surveillance, centralized storage of aggregated data leads to privacy violations. This article explains how a centralized object representation, complying with the Fair Information Practice Principles (FIP) privacy constraints, can be implemented for a video surveillance system.

: http://publica.fraunhofer.de/documents/N-142755.html