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Hier finden Sie wissenschaftliche Publikationen aus den FraunhoferInstituten. Defining dynamic bayesian networks for probabilistic situation assessment
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Postprint urn:nbn:de:0011n2194008 (1.2 MByte PDF) MD5 Fingerprint: b66b71647ce385fd183161cb211e02da © 2012 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. Erstellt am: 15.11.2012 
 Institute of Electrical and Electronics Engineers IEEE: Fusion 2012, 15th International Conference on Information Fusion : 09.15. July 2012, Singapore New York, NY: IEEE, 2012 ISBN: 9781467304177 (Print) ISBN: 9780982443842 (Online) ISBN: 9780982443859 S.888895 
 International Conference on Information Fusion (FUSION) <15, 2012, Singapore> 

 Englisch 
 Konferenzbeitrag, Elektronische Publikation 
 Fraunhofer IOSB () 
Abstract
In surveillance systems, the situation awareness of decision makers is often a crucial point in making appropriate decisions. For supporting the situation assessment process, modules performing an automatic interpretation of the observed environment can be used. However, there is still a need for an optimal solution for the definition of such modules. In this article we describe how situations of interest can be modeled in a humanunderstandable way and how their existence can be inferred from sensor observations by the use of dynamic Bayesian networks. A crucial point of modeling such networks is the definition of the parameters, namely the conditional probabilities. We present a method for an automatic definition of the parameters that can be easily used by a human operator when designing a new network. By using this approach, we define two example networks that are able to recognize situations of interest in the VIRAT dataset. Finally, the two networks are applied to the VIRAT dataset and we present an evaluation of the performance of the automatic situation assessment.