DocumentCode :
665091
Title :
Bayesian fusion: Modeling and application
Author :
Sander, Joerg ; Beyerer, Jurgen
Author_Institution :
Fraunhofer Inst. of Optronics, Syst. Technol. & Image Exploitation (IOSB), Karlsruhe, Germany
fYear :
2013
fDate :
9-11 Oct. 2013
Firstpage :
1
Lastpage :
6
Abstract :
Bayesian statistics leads to a powerful fusion methodology, especially for the fusion of heterogeneous information sources. If fusion problems are handled under consideration of the full expressiveness and the full range of methods provided by Bayesian statistics, the Bayesian fusion methodology possesses an impressive wide range of applications. We discuss this by having a closer look at selected aspects of Bayesian modeling. Thereby, also parallels to other methods used for information fusion will be drawn. With regard to the practical tractability of Bayesian fusion problems, selected approaches to deal with its potentially high complexity are discussed.
Keywords :
sensor fusion; statistical analysis; Bayesian fusion methodology; Bayesian fusion problems; Bayesian modeling; Bayesian statistics; fusion problems; heterogeneous information sources; Bayes methods; Markov processes; Probabilistic logic; Reliability; Sensors; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Sensor Data Fusion: Trends, Solutions, Applications (SDF), 2013 Workshop on
Conference_Location :
Bonn
Print_ISBN :
978-1-4799-0777-9
Type :
conf
DOI :
10.1109/SDF.2013.6698254
Filename :
6698254
Link To Document :
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