PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Learning generative texture models with extended Fields-of-Experts
Nicolas Heess, Christopher Williams and Geoffrey Hinton
In: Brtish Machine Vision Conference 2009, 7-10 Sept 2009, London, UK.


We evaluate the ability of the popular Field-of-Experts (FoE) to model structure in images. As a test case we focus on modeling synthetic and natural textures. We find that even for modeling single textures, the FoE provides insufficient flexibility to learn good generative models ­ it does not perform any better than the much simpler Gaussian FoE. We propose an extended version of the FoE (allowing for bimodal potentials) and demonstrate that this novel formulation, when trained with a better approximation of the likelihood gradient, gives rise to a more powerful generative model of specific visual structure that produces significantly better results for the texture task.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
ID Code:6021
Deposited By:Christopher Williams
Deposited On:08 March 2010