Video Based Mask Detection

Authors

  • Ryan D. Julius Student, Department of Computer Science and Engineering, CMR Technical Campus, Hyderabad, India
  • Vivek Mittal Student, Department of Computer Science and Engineering, CMR Technical Campus, Hyderabad, India
  • R. Rugved Student, Department of Computer Science and Engineering, CMR Technical Campus, Hyderabad, India

Keywords:

Deep Learning, facial land marking, MobileNet, NumPy, TensorFlow object detection module

Abstract

COVID-19 pandemic has rapidly affected our day-to-day life disrupting many different sectors of the industry. Wearing a protective face mask has become a new normal. An individual that doesn't wear a mask poses a threat to the safety of the group of people in the area. As one year has passed living with the virus it has also been shown that many individuals don't wear their mask if they are not told to do so. At this stage it is very important to ensure that each and every one of us wears a mask. In a vicinity that consists of a group of people such as schools, colleges, movie theatres etc. we can use image processing to recognize how many individuals are consistently wearing their masks. This proposed system also ensures that if an individual is to ever remove his/her mask, the relevant authority is informed about it. If deployed correctly, our product could potentially be used to help ensure our safety and the safety of others around us. This allows the college/org to be more efficient and save time compared to the standard methods available.

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Published

14-06-2021

Issue

Section

Articles

How to Cite

[1]
R. D. Julius, V. Mittal, and R. Rugved, “Video Based Mask Detection”, IJRESM, vol. 4, no. 6, pp. 117–119, Jun. 2021, Accessed: Apr. 26, 2024. [Online]. Available: https://journal.ijresm.com/index.php/ijresm/article/view/841