Corpus ID: 54488587

The Impact of Quantity of Training Data on Recognition of Eating Gestures

  title={The Impact of Quantity of Training Data on Recognition of Eating Gestures},
  author={Y. Shen and E. Muth and A. Hoover},
  • Y. Shen, E. Muth, A. Hoover
  • Published 2018
  • Computer Science, Mathematics
  • ArXiv
  • This paper considers the problem of recognizing eating gestures by tracking wrist motion. Eating gestures can have large variability in motion depending on the subject, utensil, and type of food or beverage being consumed. Previous works have shown viable proofs-of-concept of recognizing eating gestures in laboratory settings with small numbers of subjects and food types, but it is unclear how well these methods would work if tested on a larger population in natural settings. As more subjects… CONTINUE READING

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