2026-09-18T21:24:08Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/854102026-06-06T00:56:13Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Randall Davis.
Chang, Stephen M
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2014-03-06T15:40:04Z
2014-03-06T15:40:04Z
2013
2013
http://hdl.handle.net/1721.1/85410
870310033
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2013.
Cataloged from PDF version of thesis.
Includes bibliographical references (page 61).
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.
by Stephen M. Chang.
M.Eng.
61 pages
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Using gesture recognition to control PowerPoint using the Microsoft Kinect
Thesis
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