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This paper presents a new probabilistic model for the task of image annotation. Our model, which we call sLDA-bin, extends supervised Latent Dirichlet Allocation (sLDA) model to handle a multi-variate binary response variable of the annotation data. Unlike correspondence LDA (cLDA), the association model in sLDA allows each caption word to be associated with more than 1 image region and is thus more...
We present a probabilistic graphical model that learns the joint statistical structures of text, audio, and video for the purpose of classification and retrieval of multimedia documents. The proposed model, which we call Multi-modal LDA (MM-LDA), builds on the basic Latent Dirichlet Allocation (LDA) model by postulating common hidden factors, termed topics, that are shared among the 3 data modalities...
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