Mask Recognition with Computer Vision in the Age of a Pandemic

Authors

  • Daniel Jones St. John's University
  • Christoforos Christoforou

DOI:

https://doi.org/10.32473/flairs.v34i1.128486

Abstract

In the current age of coronavirus, monitoring and enforcing correct mask-wearing regulation in public spaces is of para- mount importance. Specifically, there is a need to monitor whether people wear masks and whether they wear them cor- rectly. However, there is a lack of automated systems to rec- ognize correct mask-wearing compliance. In this paper, we propose a computer-vision-based solution to the problem of mask-wearing monitoring. In particular, we propose a convo- lutional neural network to recognize images of people wear- ing masks correctly, people wearing masks incorrectly, and people not wearing masks at all. Our proposed model is shown to predict correct mask-wearing practices with over 98% accuracy. The model can be easily deployed as an auto- mated system to screen people entering indoor spaces, and can replace current manual, time-consuming, temperature- screening practices. Such applications can serve as an im- portant tool to help reduce transmission rates during the cur- rent pandemic.

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Published

2021-04-18

How to Cite

Jones, D., & Christoforou, C. (2021). Mask Recognition with Computer Vision in the Age of a Pandemic. The International FLAIRS Conference Proceedings, 34. https://doi.org/10.32473/flairs.v34i1.128486

Issue

Section

Main Track Proceedings