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An Accelerometer-based Gesture Recognition System for a Tactical Communications Application

In modern society, computers are primarily interacted with via keyboards, touch screens, voice recognition, video analysis, and many others. For certain applications, these methods may be the most efficient interface. However, there are applications that we can conceive where a more natural interface could be convenient and connect humans and computers in a more intuitive and natural way. These applications are gesture recognition systems and range from the interpretation of sign language by a computer to virtual reality control. This Thesis proposes a gesture recognition system that primarily uses accelerometers to capture gestures from a tactical communications application. A segmentation algorithm is developed based on the accelerometer energy to segment these gestures from an input sequence. Using signal processing and machine learning techniques, the segments are reduced to mathematical features and classified with support vector machines. Experimental results show that the system achieves an overall gesture recognition accuracy of 98.9%. Additional methods, such as non-gesture recognition/suppression, are also proposed and tested.

Identiferoai:union.ndltd.org:unt.edu/info:ark/67531/metadc822779
Date12 1900
CreatorsTidwell, Robert S., Jr.
ContributorsKavi, Krishna M., Akl, Robert G., Mikler, Armin
PublisherUniversity of North Texas
Source SetsUniversity of North Texas
LanguageEnglish
Detected LanguageEnglish
TypeThesis or Dissertation
Formatvii, 46 pages : illustrations (chiefly color), Text
RightsPublic, Tidwell, Robert S., Jr., Copyright, Copyright is held by the author, unless otherwise noted. All rights Reserved.

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