Computing at Glasgow University
Paper ID: 9060

Bayesian Mixture Hierarchies for Automatic Image Annotation
Stathopoulos,V. Jose,J.M.

Publication Type: Conference Proceedings
Appeared in: European Conference on Information Retrieval
Page Numbers :
Publisher: Springer
Year: 2009

Previous research on automatic image annotation has shown that accurate estimates of the class conditional densities in generative models have a positive effect in annotation performance. We focus on the problem of density estimation in the context of automatic image annotation and propose a novel Bayesian hierarchical method for estimating mixture models of Gaussian components. The proposed methodology is examined in a well-known benchmark image collection and the results demonstrate its competitiveness with the state of the art.

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