深度学习框架可从视频镜头中检测口罩

自从COVID-19全球大流行之后，在公共场所使用口罩已成为一项社会义务，并且必须确保使用口罩以确保公共安全。视频片段中的面部遮罩的检测是一项具有挑战性的任务，这主要是由于以下事实：由于遮罩区域中不存在面部标志，因此遮罩本身充当了面部检测算法的遮挡。..

Deep Learning Framework to Detect Face Masks from Video Footage

The use of facial masks in public spaces has become a social obligation since the wake of the COVID-19 global pandemic and the identification of facial masks can be imperative to ensure public safety. Detection of facial masks in video footages is a challenging task primarily due to the fact that the masks themselves behave as occlusions to face detection algorithms due to the absence of facial landmarks in the masked regions.In this work, we propose an approach for detecting facial masks in videos using deep learning. The proposed framework capitalizes on the MTCNN face detection model to identify the faces and their corresponding facial landmarks present in the video frame. These facial images and cues are then processed by a neoteric classifier that utilises the MobileNetV2 architecture as an object detector for identifying masked regions. The proposed framework was tested on a dataset which is a collection of videos capturing the movement of people in public spaces while complying with COVID-19 safety protocols. The proposed methodology demonstrated its effectiveness in detecting facial masks by achieving high precision, recall, and accuracy.