Content-based query of image databases, inspirations from text retrieval:inverted files, frequency-based weights and relevance feedback

Bibtex entry :

@inproceedings { VG:SMM1999,
    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 },
    booktitle = { The 11th Scandinavian Conference on Image Analysis },
    pages = { 143--149 },
    year = { 1999 },
    address = { Kangerlussuaq, Greenland },
    month = { jun 7--11 },
    url = { http://vision.unige.ch/publications/postscript/99/SquireMuellerMuellerRaki_scia99.ps.gz },
    abstract = { In this paper we report the application of techniques inspired bytext retrieval research to the content-based query of image databases.In particular, we show how the use of an inverted file data structurepermits the use of a feature space of $\mathcal{O}(104)$ dimensions,by restricting search to the subspace spanned by the features presentin the query. A suitably sparse set of colour and texture featuresis proposed. A scheme based on the frequency of occurrence of featuresin both individual images and in the whole collection provides ameans of weighting possibly incommensurate features in a compatiblemanner, and naturally extends to incorporate relevance feedback queries.The use of relevance feedback is shown consistently to improve systemperformance, as measured by precision and recall. },
    owner = { steph },
    timestamp = { 2008.05.04 },
    url1 = { http://vision.unige.ch/publications/postscript/99/SquireMuellerMuellerRaki_scia99.pdf },
    vgclass = { refpap },
    vgproject = { viper },
}