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

doi:10.1109/3ICT53449.2021.9581593

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

Computer And Information Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

5 Downloads (Pure)

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 language	English
Title of host publication	2021 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT)
Place of Publication	New York
Publisher	IEEE
Pages	87-92
Number of pages	6
ISBN (Electronic)	9781665440325
ISBN (Print)	9781665440332
DOIs	https://doi.org/10.1109/3ICT53449.2021.9581593
Publication status	Published - 13 Nov 2021
Event	International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies - University of Bahrain, Zallaq, Bahrain Duration: 29 Sep 2021 → 30 Sep 2021 http://iiict.uob.edu.bh/3ict21/

Conference

Conference	International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies
Abbreviated title	3ICT 2021
Country/Territory	Bahrain
City	Zallaq
Period	29/09/21 → 30/09/21
Internet address	http://iiict.uob.edu.bh/3ict21/

Keywords

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

Access to Document

10.1109/3ICT53449.2021.9581593

El-Gemayel-etal-ICT-2021-Automated-face-detection-and-control-system-using-computer-vision-based-video-analyticsAccepted author manuscript, 1.69 MB

Cite this

El Gemayel, C., Chaccour, K., & El Gemayel, J. (2021). Automated face detection and control system using computer vision based video analytics to avoid the spreading of Covid-19. In 2021 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT) (pp. 87-92). [9581593] IEEE. https://doi.org/10.1109/3ICT53449.2021.9581593

@inproceedings{41bdc58af2144b8c989a1bac499bdfcd,

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

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.",

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

author = "{El Gemayel}, Charbel and Kabalan Chaccour and {El Gemayel}, Joseph",

note = "{\textcopyright} 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.; International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies, 3ICT 2021 ; Conference date: 29-09-2021 Through 30-09-2021",

year = "2021",

month = nov,

day = "13",

doi = "10.1109/3ICT53449.2021.9581593",

language = "English",

isbn = "9781665440332",

pages = "87--92",

booktitle = "2021 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT)",

publisher = "IEEE",

url = "http://iiict.uob.edu.bh/3ict21/",

}

El Gemayel, C, Chaccour, K & El Gemayel, J 2021, Automated face detection and control system using computer vision based video analytics to avoid the spreading of Covid-19. in 2021 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT)., 9581593, IEEE, New York, pp. 87-92, International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies, Zallaq, Bahrain, 29/09/21. https://doi.org/10.1109/3ICT53449.2021.9581593

Automated face detection and control system using computer vision based video analytics to avoid the spreading of Covid-19. / El Gemayel, Charbel; Chaccour, Kabalan; El Gemayel, Joseph.

2021 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT). New York : IEEE, 2021. p. 87-92 9581593.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

TY - GEN

T1 - Automated face detection and control system using computer vision based video analytics to avoid the spreading of Covid-19

AU - El Gemayel, Charbel

AU - Chaccour, Kabalan

AU - El Gemayel, Joseph

N1 - © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

PY - 2021/11/13

Y1 - 2021/11/13

N2 - 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.

AB - 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.

KW - digital image processing

KW - artificial intelligence (AI)

KW - convolutional neural network (CNN)

KW - face detection

KW - COVID-19

KW - real-time systems

UR - http://iiict.uob.edu.bh/3ict21/

U2 - 10.1109/3ICT53449.2021.9581593

DO - 10.1109/3ICT53449.2021.9581593

M3 - Conference contribution book

SN - 9781665440332

SP - 87

EP - 92

BT - 2021 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT)

PB - IEEE

CY - New York

T2 - International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies

Y2 - 29 September 2021 through 30 September 2021

ER -

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

Abstract

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this