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Relevance feedback and term weighting schemes for content-based image retrieval
Art der Publikation: Artikel in einem Konferenzbericht
Zitat: SMM1999a
Buchtitel: Third International Conference On Visual Information Systems (VISUAL'99)
Serie: Spring Lecture Notes in Computer Science
Band: 1614
Jahr: 1999
Monat: june~2-4
Seiten: 549-556
Verlag: Springer-Verlag
Ort: Amsterdam, The Netherlands
Abriss: This paper describes the application of techniques derived from text retrieval research to the content-based querying of image databases. Specifically, the use of inverted files, frequency-based weights and relevance feedback are investigated. The use of inverted files allows very large numbers ($\geq \mathcal{O}(10^4)$) of \emph{possible} features to be used. since search is limited to the subspace spanned by the features present in the query image(s). A variety of weighting schemes used in text retrieval are employed, yielding different results. We suggest possibles modifications for their use with image databases. The use of relevance feedback was shown to improve the query results significantly, as measured by precision and recall, for all users.
Nutzerfelder: vgproject={cbir,viper}, vgclass={refpap},
Schlagworte:
Autoren Squire, David McG.
Müller, Wolfgang
Müller, Henning
Herausgeber Huijsmans, Dionysius P.
Smeulders, Arnold W. M.
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