Design and implementation of face attribute recognition system

Abstract

At present, accurate face recognition has been widely used in real scenes, such as monitoring, access control, etc., and recognition only for face attributes is also widely used in entertainment, security and social media. Therefore, the paper is based on deep convolutional neural network MTCNN for face detection and Resnet50 network for face attribute recognition. At the same time, it uses Python language to design and develop a system that implements face attribute recognition application interface. Through data experiments, the system uses a face attribute recognition model based on deep convolutional neural networks to achieve 97.32%, 71.64% and 92.13% accuracy in identifying gender, age and ethnic attributes, respectively. At the same time, the face attribute recognition application system can run stably and has certain application value.

Keywords

• deep learning; convolutional neural network; face detection; face attributes recognition; application system development