Abstract
In this paper, we propose a hierarchical Dirichlet process (HDP) mixture model of inverted Dirichlet (ID) distributions. The proposed model is learned within a principled variational Bayesian framework that we have developed by selecting appropriate priors for the parameters and calculating good approximations to the exact posteriors. The proposed statistical framework is validated via a challenging application namely multimodal person identity verification.
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Fan, W., Bouguila, N. (2016). A Nonparametric Hierarchical Bayesian Model and Its Application on Multimodal Person Identity Verification. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2016. Lecture Notes in Computer Science(), vol 10073. Springer, Cham. https://doi.org/10.1007/978-3-319-50832-0_39
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DOI: https://doi.org/10.1007/978-3-319-50832-0_39
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