Title: A New Approach to Interactive Visual Search with RBF Networks based on Preference Modelling
Authors: ROTTER Pawel
Citation: LECTURE NOTES IN ARTIFICIAL INTELLIGENCE vol. 5097 p. 861-873
Publisher: SPRINGER-VERLAG BERLIN
Publication Year: 2008
JRC N°: JRC49944
ISSN: 0302-9743
URI: http://www.springerlink.com/content/y6r4442071062h47/?p=c66e3a5f3b5a410796050413162d700d&pi=81
http://publications.jrc.ec.europa.eu/repository/handle/JRC49944
DOI: 10.1007/978-3-540-69731-2
Type: Articles in periodicals and books
Abstract: In this paper, we propose a new method for image retrieval with relevance feedback based on eliciting preferences from the decision maker aquiring visual information from an image database. The proposed extension of the common approach to image retrieval with relevance feedback allows it to be applied to objects with non-homogenous colour and texture. This has been accomplished by the algorithms, which model user queries by an RBF neural network. As an example of the application of this approach, we have used a content-based search in an atlas of species. An experimental comparision with the commonly-used content-based image retrieval approach is presented.
JRC Directorate:Growth and Innovation

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