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2016 | OriginalPaper | Chapter

View-Based 3D Objects Recognition with Expectation Propagation Learning

Authors : Adrien Bertrand, Faisal R. Al-Osaimi, Nizar Bouguila

Published in: Advances in Visual Computing

Publisher: Springer International Publishing

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Abstract

In this paper, we develop an expectation propagation learning framework for the inverted Dirichlet (ID) and Dirichlet mixture models. The main goal is to implement an algorithm to recognize 3D objects. Those objects are in our case from a view-based 3D models database that we have assembled. Following specific rules determined by analyzing the results of our tests, we have been able to get promising recognition rates. Experimental results are presented with different object classes by comparing recognition rates and confidence levels according to different tuning parameters.

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Footnotes
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Metadata
Title
View-Based 3D Objects Recognition with Expectation Propagation Learning
Authors
Adrien Bertrand
Faisal R. Al-Osaimi
Nizar Bouguila
Copyright Year
2016
Book
Advances in Visual Computing

Print ISBN: 978-3-319-50831-3

Electronic ISBN: 978-3-319-50832-0

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-50832-0_35

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