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A full-body gesture database for human gesture analysis

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dc.contributor.authorHwang, Bon-Woo-
dc.contributor.authorKim, Sungmin-
dc.contributor.authorLee, Seong-Whan-
dc.date.accessioned2021-09-09T17:09:51Z-
dc.date.available2021-09-09T17:09:51Z-
dc.date.created2021-06-10-
dc.date.issued2007-09-
dc.identifier.issn0218-0014-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/125724-
dc.description.abstractThis paper presents a full-body gesture database which contains 2D video data and 3D motion data of 14 normal gestures, 10 abnormal gestures and 30 command gestures for 20 subjects. We call this database the Korea University Gesture (KUG) database. Using 3D motion cameras and 3 sets of stereo cameras, we captured 3D motion data and 3 pairs of stereo-video data in 3 different directions for normal and abnormal gestures. In case of command gestures, 2 pairs of stereo-video data were obtained by 2 sets of stereo cameras with different focal lengths in order to capture views of whole body and upper body, simultaneously. The 2D silhouette data was synthesized by separating a subject and background in 2D stereo-video data. In this paper, we describe the gesture capture system, the organization of database, the potential usages of the database and the contact point for the KUG database. We expect that this database would be very useful for the study of 2D/3D human gesture and its application.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherWORLD SCIENTIFIC PUBL CO PTE LTD-
dc.subjectRECOGNITION-
dc.subjectMOTION-
dc.subjectPERCEPTION-
dc.titleA full-body gesture database for human gesture analysis-
dc.typeArticle-
dc.contributor.affiliatedAuthorLee, Seong-Whan-
dc.identifier.doi10.1142/S0218001407005806-
dc.identifier.scopusid2-s2.0-34548722787-
dc.identifier.wosid000251719800007-
dc.identifier.bibliographicCitationINTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, v.21, no.6, pp.1069 - 1084-
dc.relation.isPartOfINTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE-
dc.citation.titleINTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE-
dc.citation.volume21-
dc.citation.number6-
dc.citation.startPage1069-
dc.citation.endPage1084-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.subject.keywordPlusRECOGNITION-
dc.subject.keywordPlusMOTION-
dc.subject.keywordPlusPERCEPTION-
dc.subject.keywordAuthorfull body gesture database-
dc.subject.keywordAuthornormal/abnormal/command gesture-
dc.subject.keywordAuthorgesture recognition-
dc.subject.keywordAuthorhuman motion analysis-
dc.subject.keywordAuthor3D human body model-
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