1998
@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/VGTR98.04_SquireMuellerMuellerRaki.ps.gz},
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.},
}