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23 September 2009 Model-based object recognition in range imagery
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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.
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Walter Armbruster "Model-based object recognition in range imagery", Proc. SPIE 7481, Electro-Optical and Infrared Systems: Technology and Applications VI, 748102 (23 September 2009);

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