Hierarchical soft clustering tree for fast approximate search of binary codes

Cited 1 time in webofscience Cited 0 time in scopus
  • Hit : 363
  • Download : 0
DC FieldValueLanguage
dc.contributor.authorChoi, Sugilko
dc.contributor.authorLee, Suwonko
dc.contributor.authorYang, Hyun-Seungko
dc.date.accessioned2016-04-20T06:53:15Z-
dc.date.available2016-04-20T06:53:15Z-
dc.date.created2015-11-18-
dc.date.created2015-11-18-
dc.date.issued2015-11-
dc.identifier.citationELECTRONICS LETTERS, v.51, no.24, pp.1992 - 1993-
dc.identifier.issn0013-5194-
dc.identifier.urihttp://hdl.handle.net/10203/205553-
dc.description.abstractBinary codes play an important role in many computer vision applications. They require less storage space while allowing efficient computations. However, a linear search to find the best matches among binary data creates a bottleneck for large-scale datasets. Among the approximation methods used to solve this problem, the hierarchical clustering tree (HCT) method is a state-of the-art method. However, the HCT performs a hard assignment of each data point to only one cluster, which leads to a quantisation error and degrades the search performance. As a solution to this problem, an algorithm to create hierarchical soft clustering tree (HSCT) by assigning a data point to multiple nearby clusters in the Hamming space is proposed. Through experiments, the HSCT is shown to outperform other existing methods.-
dc.languageEnglish-
dc.publisherINST ENGINEERING TECHNOLOGY-IET-
dc.titleHierarchical soft clustering tree for fast approximate search of binary codes-
dc.typeArticle-
dc.identifier.wosid000365573200020-
dc.identifier.scopusid2-s2.0-84948409184-
dc.type.rimsART-
dc.citation.volume51-
dc.citation.issue24-
dc.citation.beginningpage1992-
dc.citation.endingpage1993-
dc.citation.publicationnameELECTRONICS LETTERS-
dc.identifier.doi10.1049/el.2015.2806-
dc.contributor.localauthorYang, Hyun-Seung-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorbinary codes-
dc.subject.keywordAuthorHamming codes-
dc.subject.keywordAuthorsearch problems-
dc.subject.keywordAuthorcomputer vision-
dc.subject.keywordAuthorimage coding-
dc.subject.keywordAuthorapproximation theory-
dc.subject.keywordAuthorquantisation (signal)-
dc.subject.keywordAuthorpattern clustering-
dc.subject.keywordAuthortree codes-
dc.subject.keywordAuthorhierarchical soft clustering tree-
dc.subject.keywordAuthorapproximate search-
dc.subject.keywordAuthorbinary code-
dc.subject.keywordAuthorcomputer vision-
dc.subject.keywordAuthorlinear search-
dc.subject.keywordAuthorapproximation method-
dc.subject.keywordAuthorHSCT method-
dc.subject.keywordAuthorquantisation error-
dc.subject.keywordAuthordata point assignment-
dc.subject.keywordAuthorHamming space-
Appears in Collection
CS-Journal Papers(저널논문)
Files in This Item
There are no files associated with this item.
This item is cited by other documents in WoS
⊙ Detail Information in WoSⓡ Click to see webofscience_button
⊙ Cited 1 items in WoS Click to see citing articles in records_button

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0