Automated face detection and control system using computer vision based video analytics to avoid the spreading of Covid-19

Charbel El Gemayel, Kabalan Chaccour, Joseph El Gemayel

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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Abstract

The classification of COVID-19 as global pandemic has led researchers and scientists to design solutions in order to reduce the fast spreading of the virus. This paper presents a novel detection and control system that utilizes Computer Vision based video analytics to help in reducing the speed of the spreading of the virus by recognizing people and detecting masks. The system uses the body temperature and other user biometrics to give access to a particular environment. The proposed system is able to identify a person who wants to access an environment and tracks his movement. The system can also control the door of the main entrance, the elevator, or any access zone, and generate audio notifications to alert user(s) to put their mask(s). The implementation results show that the proposed system has the advantages of a high sensitivity of 98.8% for front faces and 90.3% for turned faces, and ensure a safe environment while preserving the benefits of being modular and low cost.
Original languageEnglish
Title of host publication2021 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT)
Place of PublicationNew York
PublisherIEEE
Pages87-92
Number of pages6
ISBN (Electronic)9781665440325
ISBN (Print)9781665440332
DOIs
Publication statusPublished - 13 Nov 2021
EventInternational Conference on Innovation and Intelligence for Informatics, Computing, and Technologies - University of Bahrain, Zallaq, Bahrain
Duration: 29 Sep 202130 Sep 2021
http://iiict.uob.edu.bh/3ict21/

Conference

ConferenceInternational Conference on Innovation and Intelligence for Informatics, Computing, and Technologies
Abbreviated title3ICT 2021
Country/TerritoryBahrain
CityZallaq
Period29/09/2130/09/21
Internet address

Keywords

  • digital image processing
  • artificial intelligence (AI)
  • convolutional neural network (CNN)
  • face detection
  • COVID-19
  • real-time systems

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