DocumentCode :
3178853
Title :
Applying Sum and Max Product Algorithms of Belief Propagation to 3D Shape Matching and Registration
Author :
Xiao, Pengdong ; Barnes, Nick ; Lieby, Paulette ; Caetano, Tiberio
Author_Institution :
Res. Sch. of Inf. Sci. & Eng., Australian Nat. Univ., Canberra, ACT, Australia
fYear :
2009
fDate :
1-3 Dec. 2009
Firstpage :
387
Lastpage :
394
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.
Keywords :
Markov processes; approximation theory; belief networks; image matching; image registration; minimisation; 3D registration; 3D shape matching; Markov random field; NP-hard problem; approximation algorithms; belief propagation; energy function minimisation problem; max product algorithm; optimisation; sum product algorithm; Australia; Belief propagation; Computer applications; Databases; Digital images; Markov random fields; Minimization methods; Power engineering and energy; Shape; State-space methods; belief propagation; max product; shape matching; sum product;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital Image Computing: Techniques and Applications, 2009. DICTA '09.
Conference_Location :
Melbourne, VIC
Print_ISBN :
978-1-4244-5297-2
Electronic_ISBN :
978-0-7695-3866-2
Type :
conf
DOI :
10.1109/DICTA.2009.70
Filename :
5384933
Link To Document :
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