{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/85410"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/85410","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Using gesture recognition to control PowerPoint using the Microsoft Kinect","abstract":"This thesis describes the design and implementation of a speech and gesture recognition system used to control a PowerPoint presentation using the Microsoft Kinect. This system focuses on the identification of natural gestures that occur during a PowerPoint presentation, making the user experience as fluid as possible. The system uses an HMM to classify the performed gestures in conjunction with an SVM to perform real-time segmentation of gestures. The fusion of these two models allows the system to classify gestures in real time as they are being performed instead of waiting until completion. 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