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Bayesian fusion of multivariate image series to obtain depth information

 
: Gheta, I.; Heizmann, M.; Beyerer, J.

:
Postprint urn:nbn:de:0011-n-844213 (654 KByte PDF)
MD5 Fingerprint: 00ea405f197a25e3d044f8c920994520
© 2008 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.
Created on: 28.8.2009


Verband Deutscher Elektrotechniker e.V. -VDE-, Berlin; Informationstechnische Gesellschaft -ITG-; Forschungsgesellschaft für Angewandte Naturwissenschaften -FGAN-; Institute of Electrical and Electronics Engineers -IEEE-:
11th International Conference on Information Fusion. Proceedings. CD-ROM : Cologne, Germany, June 30 - July 03, 2008
Piscataway, NJ: IEEE, 2008
ISBN: 978-3-00-024883-2
pp.1731-1737
International Conference on Information Fusion (Fusion) <11, 2008, Cologne>
English
Conference Paper, Electronic Publication
Fraunhofer IITB ( IOSB) ()
image fusion; bayesian fusion; multivariate image series; 3d information; Bildverarbeitung

Abstract
This contribution presents a fusion method for multivariate stereo and spectral series with the purpose of obtaining 3D information. The image series are gained using a camera array with spectral filters. In order to register them, features that are invariant with respect to the intensity values in the images are extracted. The fusion approach is region based and uses characteristics like their size, position and form for registration. Regions are identified using the watershed transformation. The fusion problem is modeled by means of energy functionals and solved by applying a standard minimization algorithm. A generalization of the fusion problem is obtained by connecting it to the Bayesian fusion framework. An example of a reconstructed scene is given, showing the potential of the implemented algorithm.

: http://publica.fraunhofer.de/documents/N-84421.html