Improving web-based image search via content based clustering
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Improving web-based image search via content based clustering. / Ben-Haim, Nadav; Babenko, Boris; Belongie, Serge.
In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2006.Research output: Contribution to journal › Conference article › Research › peer-review
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TY - GEN
T1 - Improving web-based image search via content based clustering
AU - Ben-Haim, Nadav
AU - Babenko, Boris
AU - Belongie, Serge
PY - 2006
Y1 - 2006
N2 - Current image search engines on the web rely purely on the keywords around the images and the filenames, which produces a lot of garbage in the search results. Alternatively, there exist methods for content based image retrieval that require a user to submit a query image, and return images that are similar in content. We propose a novel approach named ReSPEC (Re-ranking Sets of Pictures by Exploiting Consistency), that is a hybrid of the two methods. Our algorithm first retrieves the results of a keyword query from an existing image search engine, clusters the results based on extracted image features, and returns the cluster that is inferred to be the most relevant to the search query. Furthermore, it ranks the remaining results in order of relevance.
AB - Current image search engines on the web rely purely on the keywords around the images and the filenames, which produces a lot of garbage in the search results. Alternatively, there exist methods for content based image retrieval that require a user to submit a query image, and return images that are similar in content. We propose a novel approach named ReSPEC (Re-ranking Sets of Pictures by Exploiting Consistency), that is a hybrid of the two methods. Our algorithm first retrieves the results of a keyword query from an existing image search engine, clusters the results based on extracted image features, and returns the cluster that is inferred to be the most relevant to the search query. Furthermore, it ranks the remaining results in order of relevance.
UR - http://www.scopus.com/inward/record.url?scp=33845516856&partnerID=8YFLogxK
U2 - 10.1109/CVPRW.2006.100
DO - 10.1109/CVPRW.2006.100
M3 - Conference article
AN - SCOPUS:33845516856
JO - I E E E Conference on Computer Vision and Pattern Recognition. Proceedings
JF - I E E E Conference on Computer Vision and Pattern Recognition. Proceedings
SN - 1063-6919
T2 - 2006 Conference on Computer Vision and Pattern Recognition Workshops
Y2 - 17 June 2006 through 22 June 2006
ER -
ID: 302053942