Face and Face-mask Detection System using VGG-16 Architecture based on Convolutional Neural Network
Chamandeep Vimal, Neeraj Shirivastava
Abstract
Face recognition can be used in several applications such as in surveillance, identification in login system and personalized technology. The challenge of the face detection system is the non-frontal face position and the use of accessories that cover the face area; even conventional detection systems that rely on facial features are difficult to get high accuracy. The proposed system can overcome these problems and it can detect human face with mask also. The deep learning system can recognize facial features with complex backgrounds. The VGG16 architecture based on convolutional neural network with shallow layers to produce light computing then the system can work real-time. Multiple layer detection on the last feature map is used to detect varied face sizes. The system result shows sequential images of face localization with 93% accuracy.