Analysis of face recognition technology based on deep learning

Abstract

The emergence of face recognition technology has brought great convenience to human society. After years of research and improvement, face recognition technology has matured. This paper mainly studies face recognition technology based on deep learning, and introduces five main applications, including occlusion face recognition, 3D face recognition, and expression recognition. The typical algorithms listed show that, compared with the traditional feature face algorithms and local binary patterns, algorithms such as DeepFace, FaceNet, ResNet, etc. have made significant progress in recognition efficiency and accuracy in recent years. After combining the development status of face recognition technology with the problems and security risks of the current technology, this paper proposes three solutions: increasing the amount of data, optimizing the model, and government control. In the future, legal data sharing and code open source will be major progress in this field, and dynamic face recognition technology will also be widely used.