In this work, an extensive review of literature in the field of gesture recognition carried out along with the implementation of a simple classification system for hand hygiene stages based on deep learning solutions. A subset of robust dataset that consist of handwashing gestures with two hands as well as one-hand gestures such as linear hand movement utilized. A pretrained neural network model, RES Net 50, with image net weights used for the classification of 3 categories: Linear hand movement, rub hands palm to palm and rub hands with fingers interlaced movement. Correct predictions made for the first two classes with > 60% accuracy. A complete dataset along with increased number of classes and training steps will be explored as a future work.
@article{arxiv.2108.08127,
title = {Hand Hygiene Video Classification Based on Deep Learning},
author = {Rashmi Bakshi},
journal= {arXiv preprint arXiv:2108.08127},
year = {2021}
}