TY  - RPRT
ID  - SMM1998a
T1  - Relevance feedback and term weighting schemes for content-based image retrieval
A1  - Squire, David McG.
A1  - Müller, Wolfgang
A1  - Müller, Henning
Y1  - 1998
IS  - 98.05
T2  - Computer Vision Group, Computing Centre, University of Geneva
AD  - rue G\'{e}n\'{e}ral Dufour, 24, CH-1211 Gen\`{e}ve, Switzerland
KW  - image retrieval
KW  - relevance feedback
N2  - 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.
M1  - vgproject={viper
M1  - cbir}
M1  - 
vgclass={report}
ER  -