Recognition of Human Face Regions under Adverse Conditions—Face Masks and Glasses—In Thermographic Sanitary Barriers through Learning Transfer from an Object Detector

Machines

Reginaldo B. Nunes¹  Pablo R. Muniz¹  Josemar Simão¹  Hércules L. M. Campos²  Gustavo M. de Almeida³  Marco Antonio de S. L. Cuadros³  Joabe R. da Silva³ 

[1] Department of Electrical Engineering, Federal Institute of Espírito Santo, Vitoria 29040-780, Brazil;Institute of Health and Biotechnology, Federal University of Amazonas, Coari 69460-000, Brazil;Postgraduate Program in Control and Automation Engineering, Federal Institute of Espírito Santo, Serra 29173-087, Brazil;

关键词: COVID-19;    thermography;    fever;    computer vision;    intelligent systems;    artificial intelligence;   

DOI  :  10.3390/machines10010043

来源: DOAJ

【 摘 要 】

The COVID-19 pandemic has detrimentally affected people’s lives and the economies of many countries, causing disruption in the health, education, transport, and other sectors. Several countries have implemented sanitary barriers at airports, bus and train stations, company gates, and other shared spaces to detect patients with viral symptoms in an effort to contain the spread of the disease. As fever is one of the most recurrent disease symptoms, the demand for devices that measure skin (body surface) temperature has increased. The thermal imaging camera, also known as a thermal imager, is one such device used to measure temperature. It employs a technology known as infrared thermography and is a noninvasive, fast, and objective tool. This study employed machine learning transfer using You Only Look Once (YOLO) to detect the hottest temperatures in the regions of interest (ROIs) of the human face in thermographic images, allowing the identification of a febrile state in humans. The algorithms detect areas of interest in the thermographic images, such as the eyes, forehead, and ears, before analyzing the temperatures in these regions. The developed software achieved excellent performance in detecting the established areas of interest, adequately indicating the maximum temperature within each region of interest, and correctly choosing the maximum temperature among them.

【 授权许可】

Unknown