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content-based query of image databases, inspirations from text retrieval: inverted files, frequency-based weights and relevance feedback
Art der Publikation: Technische Dokumentation
Zitat: SMM1998
Nummer: 98.04
Jahr: 1998
Monat: november
Institut: Computer Vision Group, Computing Centre, University of Geneva
Ort: rue G\'{e}n\'{e}ral Dufour, 24, CH-1211 Gen\`{e}ve, Switzerland
Abriss: 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.
Nutzerfelder: vgproject={viper,cbir}, vgclass={report},
Schlagworte:
Autoren Squire, David McG.
Müller, Wolfgang
Müller, Henning
Raki, Jilali
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