Howarth, Peter and Rüger, Stefan
Trading precision for speed: localised similarity functions.
In: 4th International Conference on Image and Video Retrieval (CIVR 2005), 20-22 July 2005, Singapore, 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.
||Published in: W.-K. Leow et al. (Eds.): CIVR 2005, LNCS 3568, pp. 415-424, 2005
||Knowledge Media Institute
||25 Oct 2011 16:14
||22 Oct 2012 15:18
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