Modelling Distributed Shape Priors by Gibbs Random Fields of Second Order

07/14/2011
by   Boris Flach, et al.
0

We analyse the potential of Gibbs Random Fields for shape prior modelling. We show that the expressive power of second order GRFs is already sufficient to express simple shapes and spatial relations between them simultaneously. This allows to model and recognise complex shapes as spatial compositions of simpler parts.

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