Hidden Markov Models have been effectively used in pattern recognition systems in the past. In this work, we identify the necessary elements to successfully use an HMM system for 3D gesture recognition regardless of the sensor device being used. So long as the sensor system itself is capable of outputting information about the 3 axes of motion (X, Y, and Z), that information can be used in this generic model for accurate, high speed gesture recognition. The proposed system works with accelerometer data, positional data and gyro data alike.
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