Open AccessOnline Multi-Layers Social Distance Detection in Iraqi Schools
Author(s) -
Abdulhakeem Qusay Albayati,
Farah F. Alkhalid,
Rafah K. Hussain
Publication year - 2021
Publication title -
türk bilgisayar ve matematik eğitimi dergisi
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.218
H-Index - 3
ISSN - 1309-4653
DOI - 10.17762/turcomat.v12i6.4815
Subject(s) - rectangle , computer science , social distance , covid-19 , computer vision , image (mathematics) , yard , artificial intelligence , mathematics , medicine , physics , geometry , disease , pathology , quantum mechanics , infectious disease (medical specialty)
In the circumstance of the COVID-19 pandemic, Prevention is better than cure, especially if the cure is not available, the first motto that all health organizations recommend is keep distances between people to prevent epidemic spread. In this paper, an online multi layers social distance detection system is proposed, the main idea is to detect distance among pupils and classify the distance to accept or not, this system treats stream video of fixed camera which monitor the whole school yard where the pupils are available, this proposed system used multi layers, the first is to make person detection using Yolo-4 approach including CNN model, and surround it by rectangle, the second is to specify the center of detected person, finally, calculate the relative distance to decide if it is accepted or not, this system works online and give high accuracy.