Content-Based Exclusion Queries in Keyword-Based Image Retrieval
by
Eisaku Yoshikawa,
Keishi Tajima
Abstract
We propose a method of evaluating exclusion queries in keyword-based
image retrieval. Image retrieval based on the presence of search
terms in the associated text can achieve high precision, while its
recall is often low because of the incompleteness of available text
data. Low recall is rarely a serious problem in Web search because
Web search is usually precision-oriented. By contrast, keyword-based
exclusion queries for image retrieval, which include negative terms
specifying what to exclude, often have low precision because of the
incomplete exclusion based on the presence of the negative terms in
incomplete text data. To avoid that, we exclude unwanted images not
based on the presence of the negative terms, but based on the
content-based similarity to images retrieved by the negative terms.
Our experiment shows that our method improves the precision of
exclusion queries in keyword-based image retrieval.
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