Description: Currently topic regression multi-mode potential Dirichlet Allocation (tr-mmLDA), image and video annotation theme of a novel statistical model task. At the heart of our new annotation model is a novel method to capture latent variable regression correlation of images or video features and comment text. Our approach is not in the data between the two modes share a set of potential topics, such as correspondence between the LDA formula, our method introduces two themes related to the return module, which captures more general form of association, and allow the data relating to the number of two different modes. We prove tr-mmLDA of two standard annotation datasets power: a 5,000-image data sets COREL sub LabelMe and a 2687 image set. Associated with the proposed model shows a title corresponding to the measured loss of improved performance compared to LDA.
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Topic Regression Multi-Modal Latent Dirichlet Allocation for Image Annotation.pdf
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