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Abstract : |
We pose the content-based retrieval problem as a problem of statistical inference and develop a Bayesian framework for indexing and retrieval in the context of large multimedia databases. All the indexing is carried out in the compressed domain and leads to efficient retrieval without compromise of the compression efficiency. The framework allows the integration of information from different sources and modalities as a way to eliminate some of the most significant limitations of the query by example search paradigm, and all the model parameters can be learned from training examples. 1, |
