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dc.contributor.authorDadgostar, F.
dc.contributor.authorSarrafzadeh, A.
dc.date.accessioned2013-05-20T02:56:31Z
dc.date.available2013-05-20T02:56:31Z
dc.date.issued2006
dc.identifier.citationDadgostar, F., Sarrafzadeh, A. (2005 [i.e. 2006]), Gesture recognition through angle space, Research Letters in the Information and Mathematical Sciences, 9, 112-119en
dc.identifier.issn1175-2777
dc.identifier.urihttp://hdl.handle.net/10179/4479
dc.description.abstractAs the notion of ubiquitous computing becomes a reality, the keyboard and mouse paradigm become less satisfactory as an input modality. The ability to interpret gestures can open another dimension in the user interface technology. In this paper, we present a novel approach for dynamic hand gesture modeling using neural networks. The results show high accuracy in detecting single and multiple gestures, which makes this a promising approach for gesture recognition from continuous input with undetermined boundaries. This method is independent of the input device and can be applied as a general back-end processor for gesture recognition systems.en
dc.language.isoenen
dc.publisherMassey Universityen
dc.subjectUser interface designen
dc.subjectHand gesture recognitionen
dc.subjectHand posture detectionen
dc.subjectUbiquitous computing
dc.titleGesture recognition through angle spaceen
dc.typeArticleen


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