• 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