Abstract: We review recent advances in image retrieval. The two fundamental components of a retrieval system, representation and learning, are analyzed. Each component is decomposed into its constituent building blocks: features, feature representation, and similarity function for the representation; short and long-term procedures for learning. We identify a series of requirements for each of the sub-areas, e.g. optimality, invariance, perceptual relevance, computational tractability, and point out various approaches proposed to satisfy them. Several open problems are also identified.
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