基于深度学习的人脸活体检测算法  

Face liveness detection algorithm based on deep learning

作　　者：黄海新[1] 张东[1] Huang Haixin;Zhang Dong(School of Automation and Electrical Engineering,Shenyang Ligong University,Shenyang 110159,China)

机构地区：[1]沈阳理工大学自动化与电器工程学院

出　　处：《电子技术应用》2019年第8期44-47,共4页Application of Electronic Technique

摘　　要：身份认证技术有了很大的发展,随之不断出现的是各种伪造合法用户信息的欺诈手段。针对这一问题,提出一种基于深度学习人脸活体检测算法,分析了真实人脸和欺诈人脸之间的区别,将真实人脸和照片进行数据去中心化、zca白化去噪声、随机旋转等处理;同时,利用卷积神经网络对照片的面部特征进行提取,提取出来的特征送入神经网络训练、分类。算法在公开的数据库NUAA上进行了验证,实验结果表明该方法降低了计算的复杂度,提高了识别准确率。Identity authentication technology has developed greatly, and there have been various fraudulent means of forging legitimate user information. Aiming at this problem, this paper proposes a deep learning face detection algorithm to analyze the difference between real face and fraud face, decentralize the real face and photo, zca whiten to noise, random rotation and other processing. At the same time, using the convolutional neural network to extract the facial features of the photos, the extracted features are sent to the neural network for training and classification. And the algorithm is verified on the public database NUAA. The experimental results show that the party reduces the calculation complexity and increases the recognition accuracy.

关 键 词：活体检测 身份认证 深度学习 人脸 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]