计算机应用与软件2018，Vol.35Issue(1)：223-231,9.DOI:10.3969/j.issn.1000-386x.2018.01.039
基于深度卷积神经网络的人脸识别技术综述
A SURVEY OF FACE RECOGNITION TECHNOLOGY BASED ON DEEP CONVOLUTIONAL NEURAL NETWORKS
摘要
Abstract
Face recognition is one of the important applications of computer vision.Generalized face recognition includes image acquisition,face detection,face alignment,and feature representation and so on.However,the development history of face recognition is mainly the history of the change of face feature representation method and summarizes the three aspects of the development history,research status and future development of face recognition technology.Firstly,reviews and summarizes several kinds of classical phases of traditional face recognition algorithm.Secondly,based on the process of the depth learning algorithm,the technical ideas and key problems of deep convolutional neural networks (DCNN),which are the breakthrough progress in face recognition,are analyzed emphatically.Based on this,the paper finally talks about the prospect of face recognition in the direction of development may exist in the future under the challenge of face recognition and deep learning algorithms.关键词
人脸识别/特征表示/深度学习/深度卷积神经网络Key words
Face recognition/Feature representation/Deep learning/DCNN分类
信息技术与安全科学引用本文复制引用
景晨凯,宋涛,庄雷,刘刚,王乐,刘凯伦..基于深度卷积神经网络的人脸识别技术综述[J].计算机应用与软件,2018,35(1):223-231,9.基金项目
国家自然科学基金项目(61379079) （61379079）
河南省国际合作项目(152102410021). （152102410021）
