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Toroidal Information Fusion Based on the Bivariate von Mises Distribution

Kurz, Gerhard 1; Hanebeck, Uwe D. 1
1 Institut für Anthropomatik und Robotik (IAR), Karlsruher Institut für Technologie (KIT)

Abstract:

Fusion of toroidal information, such as correlated
angles, is a problem that arises in many fields ranging from
robotics and signal processing to meteorology and bioinfor-
matics. For this purpose, we propose a novel fusion method
based on the bivariate von Mises distribution. Unlike most
literature on the bivariate von Mises distribution, we consider
the full version with matrix-valued parameter rather than
a simplified version. By doing so. we are able to derive
the exact analytical computation of the fusion operation. We
also propose an efficient approximation of the normalization
constant including an error bound and present a parameter
estimation algorithm based on a maximum likelihood approach.
The presented algorithms are illustrated through examples.


Originalveröffentlichung
DOI: 10.1109/MFI.2015.7295826
Scopus
Zitationen: 5
Dimensions
Zitationen: 5
Zugehörige Institution(en) am KIT Institut für Anthropomatik und Robotik (IAR)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2015
Sprache Englisch
Identifikator ISBN: 978-1-4799-7772-7
KITopen-ID: 1000051036
Erschienen in Proceedings of the 2015 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2015), 14-16 Sept. 2015, San Diego, CA , USA
Verlag Institute of Electrical and Electronics Engineers (IEEE)
Seiten 309-315
Nachgewiesen in Scopus
Dimensions
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