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dc.contributor.advisorThomassen, Asbjørn
dc.contributor.authorStøren, Henrik Hjorthen
dc.date.accessioned2017-03-13T07:37:57Z
dc.date.accessioned2017-03-13T07:37:57Z
dc.date.available2017-03-13T07:37:57Z
dc.date.available2017-03-13T07:37:57Z
dc.date.created2015-07-08
dc.date.issued2015
dc.identifierntnudaim:13899
dc.identifier.urihttp://hdl.handle.net/11250/2353633
dc.description.abstractHand gesture recognition is the task of having a machine recognize the hand gestures made by a human. In this thesis the main focus has been to research AI methods for gesture recognition. I investigate machine learning methods and image processing techniques to see if they are suited for hand gesture recognition with a color camera. I have used a PlayStation Eye camera, and written two different programs that use images captured by it to recognize and distinguish between 6 different static gestures. One of the programs uses only image processing techniques to recognize the gestures, while the other uses image processing to construct a feature vector, and then uses the KNN algorithm to predict the gesture in the image. The thesis is a proof of concept that will show the results of both programs and compare the two different approaches. I will also give a comparison between my approaches and what other researchers have done.
dc.languageeng
dc.publisherNTNU
dc.subjectDatateknologi, Intelligente systemer
dc.titleTwo-hand, camera-based gesture recognition for SoundDream
dc.typeMaster thesis


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