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Hamming embedding and weak geometric consistency for large scale image search

This paper improves recent methods for large scale image search. State of the art methods build on the bag of features image representation. We, first, analyze bag of features in the framework of approximate nearest neighbor search. This shows the suboptimality of such a representation for matching descriptors and leads us to derive a more precise representation.

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