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Content-based query of image databases, inspirations from text retrieval: inverted files, frequency-based weights and relevance feedback

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Published in The 11th Scandinavian Conference on Image Analysis. Kangerlussuaq (Greenland) - Jun 7-11 - . 1999, p. 143-149
Abstract In this paper we report the application of techniques inspired by text retrieval research to the content-based query of image databases. In particular, we show how the use of an inverted file data structure permits the use of a feature space of $\mathcal{O}(104)$ dimensions, by restricting search to the subspace spanned by the features present in the query. A suitably sparse set of colour and texture features is proposed. A scheme based on the frequency of occurrence of features in both individual images and in the whole collection provides a means of weighting possibly incommensurate features in a compatible manner, and naturally extends to incorporate relevance feedback queries. The use of relevance feedback is shown consistently to improve system performance, as measured by precision and recall.
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Research groups Viper group
Computer Vision and Multimedia Laboratory
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SQUIRE, David et al. Content-based query of image databases, inspirations from text retrieval: inverted files, frequency-based weights and relevance feedback. In: The 11th Scandinavian Conference on Image Analysis. Kangerlussuaq (Greenland). [s.l.] : [s.n.], 1999. p. 143-149. https://archive-ouverte.unige.ch/unige:47931

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Deposited on : 2015-03-06

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