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Trading precision for speed: localised similarity functions

Howarth, Peter and Rüger, Stefan (2005). Trading precision for speed: localised similarity functions. In: Image and Video Retrieval, pp. 415–424.

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We have generalised a class of similarity measures that are designed to address the problems associated with indexing high-dimensional feature space. The features are stored and indexed componentwise. For each dimension we retrieve only those objects close the query point and then apply a local distance function to this subset. Thus we can dramatically reduce the amount of data looked at.We have evaluated these distance measures within a content-based image retrieval (CBIR) framework to determine the trade-o� between the percentage of the data retrieved and the precision. Our results show that up to 90% of the data can be ignored whilst maintaining, and in some cases improving, retrieval performance.

Item Type: Conference or Workshop Item
Copyright Holders: 2005 Springer-Verlag
ISSN: 0302-9743
Extra Information: Published in: W.-K. Leow et al. (Eds.): CIVR 2005, LNCS 3568, pp. 415-424, 2005
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 29874
Depositing User: Stefan Rüger
Date Deposited: 25 Oct 2011 16:14
Last Modified: 02 May 2018 13:32
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