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.
['Pengdong Xiao', 'Nick Barnes', 'Paulette Lieby', 'Tibério S. Caetano']
Applying Sum and Max Product Algorithms of Belief Propagation to 3D Shape Matching and Registration