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Please use this identifier to cite or link to this item: http://eprint.iitd.ac.in/handle/2074/1207

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dc.contributor.authorRamamoorthy, Aditya-
dc.contributor.authorVaswani, Namrata-
dc.contributor.authorChaudhury, Santanu-
dc.contributor.authorBanerjee, Subhashis-
dc.date.accessioned2006-01-24T03:49:20Z-
dc.date.available2006-01-24T03:49:20Z-
dc.date.issued2003-
dc.identifier.citationPattern Recognition, 36(9), 2069-2081en
dc.identifier.urihttp://eprint.iitd.ac.in/dspace/handle/2074/1207-
dc.description.abstractThis paper is concerned with the problem of recognition of dynamic hand gestures. We have considered gestures which are sequences of distinct hand poses. In these gestures hand poses can undergo motion and discrete changes. However, continuous deformations of the hand shapes are not permitted. We have developed a recognition engine which can reliably recognize these gestures despite individual variations. The engine also has the ability to detect start and end of gesture sequences in an automated fashion. The recognition strategy uses a combination of static shape recognition (performed using contour discriminant analysis), Kalman filter based hand tracking and a HMM based temporal characterization scheme. The system is fairly robust to background clutter and uses skin color for static shape recognition and tracking. A real time implementation on standard hardware is developed. Experimental results establish the effectiveness of the approach.en
dc.format.extent559979 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoenen
dc.subjectHand gestureen
dc.subjectHidden Markov modelen
dc.subjectContour trackingen
dc.subjectReal time systemen
dc.titleRecognition of dynamic hand gesturesen
dc.typeArticleen
Appears in Collections:Electrical Engineering

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