基于变分自编码器的人脸表情识别  

FACIAL EXPRESSION RECOGNITION BASED ON VARIATIONAL AUTOENCODER

作　　者：党宏社[1] 王淼 陆馨蕊 王汝明 Dang Hongshe;Wang Miao;Lu Xinrui;Wang Ruming(School of Electrical and Control Engineering,Shaanxi University of Science and Technology,Xi’an 710021,Shaanxi,China;Weifang Ensign Industry Co.,Ltd.,Weifang 262400,Shandong,China)

机构地区：[1]陕西科技大学电气与控制工程学院,陕西西安710021 [2]潍坊英轩实业有限公司,山东潍坊262400

出　　处：《计算机应用与软件》2023年第7期198-202,259,共6页Computer Applications and Software

基　　金：陕西省自然科学基金项目(2020JM-509)。

摘　　要：为了在样本量较小的表情数据集上实现较高准确率的表情识别,将无监督特征学习应用于表情识别中,在传统自编码器网络的基础上,将变分自编码器引入人脸表情识别中,提出一种基于变分自编码器改进的人脸表情识别方法,使用大量无表情标签的人脸数据集对变分自编码器进行无监督训练,将变分自编码器中编码网络部分输出的低维特征输入到卷积神经网络中,由变分自编码器的编码网络和卷积神经网络两部分构成完整的表情识别网络;使用带表情标签的人脸表情数据集对网络进行训练。在CK+、JAFFE数据库进行分类实验,实验结果表明,该算法具有一定的表情识别能力。In order to achieve high accuracy expression recognition on expression data set with small sample size,unsupervised feature learning is applied to expression recognition.On the basis of traditional self encoder network,variational autoencoder was introduced into facial expression recognition.A facial expression recognition method based on improved variational autoencoder was proposed.A large number of facial data sets without expression labels were used to train the variational autoencoder unsupervised.The low-dimensional features which were output from the encoding network part of the variational autoencoder were put into the convolutional neural network,and a complete expression recognition network was composed of the encoding network and the convolutional neural network.The facial expression dataset with expression tags was used to train the network.The classification experiments were conducted on CK+and JAFFE databases.The results show that this algorithm has a certain ability of expression recognition.

关 键 词：计算机 表情识别 变分自编码器 无监督 卷积神经网络 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]