Ballroom Dance Movement Recognition Using a Smart Watch

• URL: http://arxiv.org/abs/2008.10122v2
• Date: Fri, 4 Sep 2020 05:25:56 GMT
• Title: Ballroom Dance Movement Recognition Using a Smart Watch
• Authors: Varun Badrinath Krishna
• Abstract summary: We present a whole body movement detection study using a single smart watch in the context of ballroom dancing. Deep learning representations are used to classify well-defined sequences of movements. The classification accuracy of 85.95% was improved to 92.31% by modeling a dance as a first-order Markov chain of figures.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Inertial Measurement Unit (IMU) sensors are being increasingly used to detect human gestures and movements. Using a single IMU sensor, whole body movement recognition remains a hard problem because movements may not be adequately captured by the sensor. In this paper, we present a whole body movement detection study using a single smart watch in the context of ballroom dancing. Deep learning representations are used to classify well-defined sequences of movements, called \emph{figures}. Those representations are found to outperform ensembles of random forests and hidden Markov models. The classification accuracy of 85.95\% was improved to 92.31\% by modeling a dance as a first-order Markov chain of figures and correcting estimates of the immediately preceding figure.

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