Analysis of face detection, face landmarking, and face recognition performance with masked face images
It addresses a practical problem for face recognition systems during the COVID-19 pandemic, but is incremental as it applies existing methods to new data.
This paper analyzed the impact of face masks on face detection, landmarking, and recognition performance, finding that masks negatively affect all three tasks.
Face recognition has become an essential task in our lives. However, the current COVID-19 pandemic has led to the widespread use of face masks. The effect of wearing face masks is currently an understudied issue. The aim of this paper is to analyze face detection, face landmarking, and face recognition performance with masked face images. HOG and CNN face detectors are used for face detection in combination with 5-point and 68-point face landmark predictors and VGG16 face recognition model is used for face recognition on masked and unmasked images. We found that the performance of face detection, face landmarking, and face recognition is negatively impacted by face masks