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dc.contributor.authorDadgostar, F
dc.contributor.authorSarrafzadeh, Hossein
dc.date.accessioned2013-08-26T02:10:05Z
dc.date.available2013-08-26T02:10:05Z
dc.date.issued2009
dc.identifier.urihttps://hdl.handle.net/10652/2297
dc.description.abstract"This paper presents research leading to the development of a vision-based gesture recognition system. The system comprises of three abstracts layers each with their own specific type and requirements of data ..."en_NZ
dc.language.isoenen_NZ
dc.subjectadaptive skin detectionen_NZ
dc.subjecthue color spaceen_NZ
dc.subjectmean-shift algorithmen_NZ
dc.subjectobject trackingen_NZ
dc.subjectgesture recognitionen_NZ
dc.subjectneural networksen_NZ
dc.titleHand and Face Tracking for Gesture Recognitionen_NZ
dc.typeJournal Articleen_NZ
dc.rights.holderAuthor, Australian Journal of Intelligent Information Processing Systems.en_NZ
dc.subject.marsden080201 Analysis of Algorithms and Complexityen_NZ
dc.identifier.bibliographicCitationDadgostar, F., Sarrafzadeh, A., and Messom, C. (2009). Hand and Face Tracking for Gesture Recognition. Australian Journal of Intelligent Information Processing Systems.en_NZ
unitec.institutionUnitec Institute of Technologyen_NZ
unitec.publication.titleAustralian Journal of Intelligent Information Processing Systems.en_NZ
unitec.peerreviewedyesen_NZ
unitec.identifier.roms50195
unitec.institution.studyareaComputing


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