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Article: Joint optimization toward effective and efficient image search

TitleJoint optimization toward effective and efficient image search
Authors
KeywordsBag-of-words (BoW)
Embedding method
High effectiveness
High efficiency
Large scale image search
Issue Date2013
Citation
IEEE Transactions on Cybernetics, 2013, v. 43, n. 6, p. 2216-2227 How to Cite?
AbstractThe bag-of-words (BoW) model has been known as an effective method for large-scale image search and indexing. Recent work shows that the performance of the model can be further improved by using the embedding method. While different variants of the BoW model and embedding method have been developed, less effort has been made to discover their underlying working mechanism. In this paper, we systematically investigate the image search performance variation with respect to a few factors of the BoW model, and study how to employ the embedding method to further improve the image search performance. Subsequently, we summarize several observations based on the experiments on descriptor matching. To validate these observations in a real image search, we propose an effective and efficient image search scheme, in which the BoW model and embedding method are jointly optimized in terms of effectiveness and efficiency by following these observations. Our comprehensive experiments demonstrate that it is beneficial to employ these observations to develop an image search algorithm, and the proposed image search scheme outperforms state-of-the-art methods in both effectiveness and efficiency. © 2013 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/321540
ISSN
2023 Impact Factor: 9.4
2023 SCImago Journal Rankings: 5.641
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorWei, Shikui-
dc.contributor.authorXu, Dong-
dc.contributor.authorLi, Xuelong-
dc.contributor.authorZhao, Yao-
dc.date.accessioned2022-11-03T02:19:38Z-
dc.date.available2022-11-03T02:19:38Z-
dc.date.issued2013-
dc.identifier.citationIEEE Transactions on Cybernetics, 2013, v. 43, n. 6, p. 2216-2227-
dc.identifier.issn2168-2267-
dc.identifier.urihttp://hdl.handle.net/10722/321540-
dc.description.abstractThe bag-of-words (BoW) model has been known as an effective method for large-scale image search and indexing. Recent work shows that the performance of the model can be further improved by using the embedding method. While different variants of the BoW model and embedding method have been developed, less effort has been made to discover their underlying working mechanism. In this paper, we systematically investigate the image search performance variation with respect to a few factors of the BoW model, and study how to employ the embedding method to further improve the image search performance. Subsequently, we summarize several observations based on the experiments on descriptor matching. To validate these observations in a real image search, we propose an effective and efficient image search scheme, in which the BoW model and embedding method are jointly optimized in terms of effectiveness and efficiency by following these observations. Our comprehensive experiments demonstrate that it is beneficial to employ these observations to develop an image search algorithm, and the proposed image search scheme outperforms state-of-the-art methods in both effectiveness and efficiency. © 2013 IEEE.-
dc.languageeng-
dc.relation.ispartofIEEE Transactions on Cybernetics-
dc.subjectBag-of-words (BoW)-
dc.subjectEmbedding method-
dc.subjectHigh effectiveness-
dc.subjectHigh efficiency-
dc.subjectLarge scale image search-
dc.titleJoint optimization toward effective and efficient image search-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/TCYB.2013.2245890-
dc.identifier.pmid23757530-
dc.identifier.scopuseid_2-s2.0-84890021527-
dc.identifier.volume43-
dc.identifier.issue6-
dc.identifier.spage2216-
dc.identifier.epage2227-
dc.identifier.isiWOS:000327647500058-

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