In the last two years, millions of lives have been lost due to COVID-19. Despite the vaccination programmes for a year, hospitalization rates and deaths are still high due to the new variants of COVID-19. Stringent guidelines and COVID-19 screening measures such as temperature check and mask check at all public places are helping reduce the spread of COVID-19. Visual inspections to ensure these screening measures can be taxing and erroneous. Automated inspection ensures an effective and accurate screening.
To perform automated screening, thermal based screening is effective as it is illumination independent and can work even under no lighting conditions. This NTIC screening dataset consists of thermal images of persons walking into public premises like offices, malls and railway stations. The ground truth consists of annotations of human faces and whether they are masks or not. Broadly, this dataset is divided into 3 sub-datasets: Thermal Surveillance Dataset: 902 thermal images with 1354 people wearing masks and 213 people without masks Augmented Surveillance Dataset: 543 images with 434 people wearing masks and 109 people without masks Lighting Dataset: 420 thermal images and their corresponding visual images.
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