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Applying Sum and Max Product Algorithms of Belief Propagation to 3D Shape Matching and Registration

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Date

2009

Authors

Xiao, Pengdong
Barnes, Nick
Lieby, Paulette
Caetano, Tiberio

Journal Title

Journal ISSN

Volume Title

Publisher

Institute of Electrical and Electronics Engineers (IEEE Inc)

Abstract

3D shape matching based on meshed surfaces can be formulated as an energy function minimisation problem under a Markov random field (MRF) framework. However, to solve such a global optimisation problem is NP-hard. So research mainly focuses on approximation algorithms. One of the best known is belief propagation (BP), which has shown success in early vision and many other practical applications. In this paper, we investigate the application of both sum and max product algorithms of belief propagation to 3D shape matching. We also apply the 3D shape matching results to a 3D registration problem.

Description

Keywords

Keywords: 3D registration; 3D shape matching; Belief propagation; Early vision; Energy functions; Global optimisation; Markov random field; Max-product; Max-product algorithms; NP-hard; Shape matching; Sum product; Approximation algorithms; Computational complexity Belief propagation; Max product; Shape matching; Sum product

Citation

URI

http://hdl.handle.net/1885/55858

Collections

ANU Research Publications

Source

Proceedings of the Digital Image Computing: Techniques and Applications (DICTA 2009)

Type

Conference paper

Book Title

Entity type

Access Statement

License Rights

DOI

10.1109/DICTA.2009.70

Restricted until

2037-12-31

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01_Xiao_Applying_Sum_and_Max_Product_2009.pdf (769.42 KB)

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