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Conceptual image retrieval over a large scale database
Abstract Image retrieval in large-scale databases iImage retrieval in large-scale databases is currently based on a textual chains matching procedure. However, this approach requires an accurate annotation of images, which is not the case on the Web. To tackle this issue, we propose a reformulation method that reduces the influence of noisy image annotations. We extract a ranked list of related concepts for terms in the query from WordNet and Wikipedia, and use them to expand the initial query. Then some visual concepts are used to re-rank the results for queries containing, explicitly or implicitly, visual cues. First evaluations on a diversified corpus of 150000 images were convincing since the proposed system was ranked 4 th and 2 nd at the WikipediaMM task of the ImageCLEF 2008 campaign [1].M task of the ImageCLEF 2008 campaign [1].
Abstractsub Image retrieval in large-scale databases iImage retrieval in large-scale databases is currently based on a textual chains matching procedure. However, this approach requires an accurate annotation of images, which is not the case on the Web. To tackle this issue, we propose a reformulation method that reduces the influence of noisy image annotations. We extract a ranked list of related concepts for terms in the query from WordNet and Wikipedia, and use them to expand the initial query. Then some visual concepts are used to re-rank the results for queries containing, explicitly or implicitly, visual cues. First evaluations on a diversified corpus of 150000 images were convincing since the proposed system was ranked 4 th and 2 nd at the WikipediaMM task of the ImageCLEF 2008 campaign [1].M task of the ImageCLEF 2008 campaign [1].
Bibtextype inproceedings  +
Doi 10.1007/978-3-642-04447-2_100  +
Has author Adrian Popescu + , Le Borgne H. + , Moellic P.-A. +
Has extra keyword ImageCLEF + , Large-scale database + , Noisy image + , Visual concept + , Visual cues + , Wikipedia + , Wordnet + , Database systems + , Image analysis + , Linguistics + , Image retrieval +
Has keyword Image retrieval + , Large-scale database + , Query reformulation +
Isbn 3642044468; 9783642044465  +
Language English +
Number of citations by publication 0  +
Number of references by publication 0  +
Pages 771–778  +
Published in Lecture Notes in Computer Science +
Title Conceptual image retrieval over a large scale database +
Type conference paper  +
Volume 5706 LNCS  +
Year 2009 +
Creation dateThis property is a special property in this wiki. 7 November 2014 20:10:00  +
Categories Publications without license parameter  + , Publications without remote mirror parameter  + , Publications without archive mirror parameter  + , Publications without paywall mirror parameter  + , Conference papers  + , Publications without references parameter  + , Publications  +
Modification dateThis property is a special property in this wiki. 7 November 2014 20:10:00  +
DateThis property is a special property in this wiki. 2009  +
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