mnmDTW: An extension to Dynamic Time Warping for Camera-based Movement Error Localization

Sebastian Dill, Maurice Rohr
10/13/2023
cs.CVcs.AI

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Abstract

In this proof of concept, we use Computer Vision (CV) methods to extract pose information out of exercise videos. We then employ a modified version of Dynamic Time Warping (DTW) to calculate the deviation from a gold standard execution of the exercise. Specifically, we calculate the distance between each body part individually to get a more precise measure for exercise accuracy. We can show that exercise mistakes are clearly visible, identifiable and localizable through this metric.

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Cite this paper

@article{dill2023mnmdtw,
  title  = {mnmDTW: An extension to Dynamic Time Warping for Camera-based Movement Error Localization},
  author = {Sebastian Dill and Maurice Rohr},
  year   = {2023},
  eprint = {2310.09170},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2310.09170v1}
}

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