Improvement of Face Recognition Accuracy for Mask Wearers

With the spread of COVID-19, wearing masks has become mandatory in many countries around the world, and there is a need for technology to recognize facial images of people wearing masks. In this paper, we conducted experiments on learning and recognizing images of mask wearers using a method based on a pre-trained model produced by NVIDIA, and studied the recognition of face images by increasing the number of datasets using data augmentation. The experimental results show the effectiveness of the proposed method, and the proposed method is implemented on NVIDIA Jetson Xavier for real-time recognition experiments.