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Proceedings Paper

Model-based object recognition in range imagery
Author(s): Walter Armbruster
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Paper Abstract

The paper formulates the mathematical foundations of object discrimination and object re-identification in range image sequences using Bayesian decision theory. Object discrimination determines the unique model corresponding to each scene object, while object re-identification finds the unique object in the scene corresponding to a given model. In the first case object identities are independent; in the second case at most one object exists having a given identity. Efficient analytical and numerical techniques for updating and maximizing the posterior distributions are introduced. Experimental results indicate to what extent a single range image of an object can be used for re-identifying this object in arbitrary scenes. Applications including the protection of commercial vessels against piracy are discussed.

Paper Details

Date Published: 23 September 2009
PDF: 11 pages
Proc. SPIE 7481, Electro-Optical and Infrared Systems: Technology and Applications VI, 748102 (23 September 2009); doi: 10.1117/12.830299
Show Author Affiliations
Walter Armbruster, FGAN-FOM (Germany)


Published in SPIE Proceedings Vol. 7481:
Electro-Optical and Infrared Systems: Technology and Applications VI
David A. Huckridge; Reinhard R. Ebert, Editor(s)

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