2000
@article{SMM2000a,
vgclass = {refpap},
vgproject = {cbir,viper},
author = {David McG.\ Squire and Wolfgang M\"{u}ller and Henning
M\"{u}ller and Thierry Pun},
title = {Content-based query of image databases: inspirations from
text retrieval},
journal = {Pattern Recognition Letters},
volume = {21},
number = {13--14},
pages = {1193--1198},
year = {2000},
note = {(Special edition: invited expanded papers from SCIA'99)},
doi = {https://doi.org/10.1016/S0167-8655(00)00081-7},
url = {http://dx.doi.org/10.1016/S0167-8655(00)00081-7},
abstract = {This paper reports the application of techniques inspired
by text retrieval research to content-based image retrieval. In
particular, we show how the use of an inverted file data structure
permits the use of an extremely high-dimensional feature-space, 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 weighting scheme based on feature frequencies is used to
combine disparate 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.},
}