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Using gesture recognition to control PowerPoint using the Microsoft Kinect

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. The incorporation of speech commands
gives the user an additional level of precision and control over
the system. This system can navigate through a PowerPoint
presentation and has a limited control over slide
animations.