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A novel architecture for behavior/event detection in security and safety management systems
Author(s): Konstantinos Georgios Thanos; Constantinos Rizogiannis; John Bothos; Dimitris M. Kyriazanos; Andreas Zalonis; Stelios C. A. Thomopoulos
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Paper Abstract

In this paper the architecture of an autonomous human behavior detection system is presented. The proposed system architecture is intended for Security and Safety surveillance systems that aim to identify adverse events or behaviors which endanger the safety of people or their well-being. Applications include monitoring systems for crowded places (Malls, Mass transport systems, other), critical infrastructures, or border crossing points. The proposed architecture consists of three modules: (a) the event detection module combined with a data fusion component responsible for the fusion of the sensor inputs along with relevant high level metadata, which are pre-defined features that are correlated with a suspicious event, (b) an adaptive learning module which takes inputs from official personnel or healthcare personnel about the correctness of the detected events, and uses it in order to properly parameterise the event detection algorithm, and (c) a statistical and stochastic analysis component which is responsible for specifying the appropriate features to be used by the event detection module. Statistical analysis estimates the correlations between the features employed in the study, while stochastic analysis is used for the estimation of dependencies between the features and the achieved system performance.

Paper Details

Date Published: 27 April 2018
PDF: 8 pages
Proc. SPIE 10646, Signal Processing, Sensor/Information Fusion, and Target Recognition XXVII, 106460V (27 April 2018); doi: 10.1117/12.2307079
Show Author Affiliations
Konstantinos Georgios Thanos, National Ctr. for Scientific Research Demokritos (Greece)
Constantinos Rizogiannis, National Ctr. for Scientific Research Demokritos (Greece)
John Bothos, National Ctr. for Scientific Research Demokritos (Greece)
Dimitris M. Kyriazanos, National Ctr. for Scientific Research Demokritos (Greece)
Andreas Zalonis, National Ctr. for Scientific Research Demokritos (Greece)
Stelios C. A. Thomopoulos, National Ctr. for Scientific Research Demokritos (Greece)


Published in SPIE Proceedings Vol. 10646:
Signal Processing, Sensor/Information Fusion, and Target Recognition XXVII
Ivan Kadar, Editor(s)

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