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The authors propose a gesture recognition system based primarily on a single 3-axis accelerometer. The system employs dynamic time warping and affinity propagation algorithms for training and utilizes the sparse nature of the gesture sequence by implementing compressive sensing for gesture recognition. A dictionary of 18 gestures or classes is defined and a database of over 3,700 repetitions is created from 7 users. Their dictionary of gestures is the largest in published studies related to acceleration-based gesture recognition, to the best of their knowledge.
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