DocumentCode :
398626
Title :
Relevance feedback for shape query refinement
Author :
Cheikh, Faouzi Alayu ; Cramariuc, B. ; Gabbouj, Moncef
Author_Institution :
Signal Process. Lab., Tampere Univ. of Technol., Finland
Volume :
1
fYear :
2003
fDate :
14-17 Sept. 2003
Abstract :
In this paper we propose to incorporate a feedback loop, into the ordinal correlation framework and apply it to shape-based image retrieval. The user´s feedback on the relevance of the retrieval results is used to tune the weights of the similarity measure. Statistics from the features of both relevant and irrelevant items are used to estimate the weights. Moreover, the information accumulated from previous retrieval iterations is used in the weights estimation. A simple measure of the discrimination power is proposed and used to show that the relevance feedback increases the capability of the ordinal correlation scheme to discriminate between relevant and irrelevant objects.
Keywords :
image retrieval; relevance feedback; correlation framework; feedback loop; relevance feedback; retrieval iteration; shape query refinement; shape-based image retrieval; similarity measure; weight estimation; Content based retrieval; Feedback loop; Humans; Image retrieval; Information retrieval; Laboratories; Pixel; Shape; Signal processing; Statistics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 2003. ICIP 2003. Proceedings. 2003 International Conference on
ISSN :
1522-4880
Print_ISBN :
0-7803-7750-8
Type :
conf
DOI :
10.1109/ICIP.2003.1247069
Filename :
1247069
Link To Document :
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