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In this paper, we present an unsupervised learning method, based on the finite Dirichlet mixture model and the bag-of-visual words representation, for categorizing human action videos. The proposed Bayesian model is learned through a principled variational framework. A variational form of the Deviance Information Criterion (DIC) is incorporated within the proposed statistical framework for evaluating...
In this paper, we propose a Bayesian nonparametric approach for modeling and selection based on the mixture of Dirichlet processes with Dirichlet distributions, which can also be considered as an infinite Dirichlet mixture model. The proposed model adopts a stick-breaking representation of the Dirichlet process and is learned through a variational inference method. In our approach, the determination...
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