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Technical Reports


  • @techreport{SMM1998,
    	vgclass =	{report},
    	vgproject =	{viper,cbir},
    	author =	{David McG. Squire and Wolfgang M\"{u}ller and Henning M\"{u}ller and Jilali Raki},
    	title =	{Content-based query of image databases, inspirations from text retrieval: inverted files, frequency-based weights and relevance feedback},
    	number =	{98.04},
    	institution =	{Computer Vision Group, Computing Centre, University of Geneva},
    	address =	{rue G\'{e}n\'{e}ral Dufour, 24, CH-1211 Gen\`{e}ve, Switzerland},
    	month =	{November},
    	year =	{1998},
    	url =	{/publications/postscript/1998/VGTR98.04_SquireMuellerMuellerRaki.pdf},
    	url1 =	{/publications/postscript/1998/},
    	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 $\mathcal{O}(10^4)$
    	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.},