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The problem of large-scale image search has been traditionally addressed with the bag-of-visual-words (BOV). In this article, we propose to use as an alternative the Fisher kernel framework. We first show why the Fisher representation is well-suited to the retrieval problem: it describes an image by what makes it different from other images. One drawback of(More)
We introduce a novel algorithm for local contrast enhancement. The algorithm exploits a background image which is estimated with an edge-preserving filter. The background image controls a gain which enhances important details hidden in underexposed regions of the input image. Our designs for the gain, edge-preserving filter and chrominance recovery avoid(More)
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