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Latent Variable Models for Content-Based Image Retrieval and Structure Prediction

Latent Variable Models for Content-Based Image Retrieval and Structure Prediction

This video was recorded at British Machine Vision Conference (BMVC), Surrey 2012. In the first part of the talk I will present recent work on learning latent variable models for content-based image retrieval. To learn a function that predicts the relevance of a database image to an image query all that we need is some form of feedback from users of the retrieval system. For example, we can obtain triplet constraints specifying that relative to some query Q, an image A should be ranked higher than an image B. When such feedback is available ranking SVMs can be used to induce the retrieval function. I will describe an extension of this framework where instead of learning a single relevance function we learn a mixture of relevance functions. Intuitively, given a query we first compute a... Show More

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