Local binary pattern based features for sign language recognition

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dc.contributor.authorHrúz, Marek
dc.contributor.authorTrojanová, Jana
dc.contributor.authorŽelezný, Miloš
dc.date.accessioned2016-01-08T09:04:18Z
dc.date.available2016-01-08T09:04:18Z
dc.date.issued2011
dc.description.abstract-translatedIn this paper we focus on appearance features describing the manual component of Sign Language particularly the Local Binary Patterns. We compare the performance of these features with geometric moments describing the trajectory and shape of hands. Since the non-manual component is also very important for sign recognition we localize facial landmarks via Active Shape Model combined with Landmark detector that increases the robustness of model fitting. We test the recognition performance of individual features and their combinations on a database consisting of 11 signers and 23 signs with several repetitions. Local Binary Patterns outperform the geometric moments. When the features are combined we achieve a recognition rate up to 99.75% for signer dependent tests and 57.54% for signer independent tests.en
dc.format12 s.cs
dc.format.mimetypeapplication/pdf
dc.identifier.citationHRÚZ, Marek; TROJANOVÁ, Jana; ŽELEZNÝ, Miloš. Local binary pattern based features for sign language recognition. In: Pattern recognition and image analysis, 22, 4, p. 519-526. ISSN 1054-6618.en
dc.identifier.issn1054-6618
dc.identifier.urihttp://www.kky.zcu.cz/cs/publications/HruzMarek_2011_LocalBinaryPattern
dc.identifier.urihttp://hdl.handle.net/11025/17183
dc.language.isoenen
dc.publisherMaik nauka-interperiodica publishingen
dc.rights© Marek Hrúz - Jana Trojanová - Miloš Železnýcs
dc.rights.accessopenAccessen
dc.subjectlocal binary patternscs
dc.subjectznaková řečcs
dc.subject.translatedlocal binary patternsen
dc.subject.translatedsign languageen
dc.titleLocal binary pattern based features for sign language recognitionen
dc.typečlánekcs
dc.typearticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen

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