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dc.contributor.advisorBanerjee, Asim
dc.contributor.authorSharma, Harish
dc.date.accessioned2017-06-10T14:39:01Z
dc.date.available2017-06-10T14:39:01Z
dc.date.issued2011
dc.identifier.citationSharma, Harish (2011). Back-view based visual hand gesture recognition system. Dhirubhai Ambani Institute of Information and Communication Technology, vii, 37 p. (Acc.No: T00304)
dc.identifier.urihttp://drsr.daiict.ac.in/handle/123456789/341
dc.description.abstractGesture recognition is a fascinating area of research due to its applications to HCI (human computer interaction), entertainment, and communication between deaf/ mute people etc. Gesture can be dynamic or static depending upon the application. Static gestures can be called postures. Dynamic gestures are collection or sequence of postures. Our method is an attempt to classify various postures in American Sign Language (ASL) for a wearable computer device like “Sixth Sense” (developed at MIT media lab) [17]. We are working with new set of features including verticalhorizontal histogram of a posture-shape. We are using Linear Discriminant Analyzer (LDA) Classifier for the purpose of classification. Also, our work is an attempt to raise some issues regarding the kind of problem that can rise during posture-shape recognition and how a simple classification technique with a new feature set can give fairly good results.
dc.publisherDhirubhai Ambani Institute of Information and Communication Technology
dc.subjectHuman-computer interaction
dc.subjectComputer vision
dc.subjectHuman-machine systems
dc.subjectGesture-Data processing
dc.subjectGesture tracking
dc.subjectHand tracking
dc.subjectSign language interpretation
dc.subjectAmerican Sign Language
dc.subjectData processing Computer science
dc.classification.ddc006.37 SHA
dc.titleBack-view based visual hand gesture recognition system
dc.typeDissertation
dc.degreeM. Tech
dc.student.id200911045
dc.accession.numberT00304


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