[1]植炜基,刘春雨,郑婉君,等.基于生成对抗网络的人脸表情识别技术综述[J].计算机技术与发展,2021,31(增刊):1-7.[doi:10. 3969 / j. issn. 1673-629X. 2021. S. 001]
　ZHI Wei-ji,LIU Chun-yu,ZHENG Wan-jun,et al.Survey of Facial Expression Recognition Technology Based onGenerative Adversarial Network[J].,2021,31(增刊):1-7.[doi:10. 3969 / j. issn. 1673-629X. 2021. S. 001]
点击复制

基于生成对抗网络的人脸表情识别技术综述()
分享到：

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
31
期数:
2021年增刊
页码:
1-7
栏目:
综述
出版日期:
2021-12-31

文章信息/Info

Title:
Survey of Facial Expression Recognition Technology Based onGenerative Adversarial Network
文章编号:
1673-629X(2021)S0001-07
作者:
植炜基1 ; 刘春雨1 ; 郑婉君2 ; 张 敏1 ; 詹思宇1
1. 深圳大学 物理与光电工程学院,广东 深圳 518000;
2. 广东科学技术职业学院,广东 珠海 519090
Author(s):
ZHI Wei-ji1 ; LIU Chun-yu1 ; ZHENG Wan-jun2 ; ZHANG Min1 ; ZHAN Si-yu1
1. School of Physics and Optoelectronic Engineering,Shenzhen University,Shenzhen 518000,China;
2. Guangdong Polytechnic of Science and Technology,Zhuhai 519090,China
关键词:
人脸表情识别; 人机交互; 深度学习; 生成对抗网络
Keywords:
facial expression recognition; human-computer interaction; deep learning; generative adversial network
分类号:
TP391
DOI:
10. 3969 / j. issn. 1673-629X. 2021. S. 001
摘要:
人脸表情识别目前在人机交互、智能控制、安全和心理等领域具有广泛的应用,而深度学习的发展更是使得人脸表情识别技术取得了巨大进步。 但是人脸表情识别技术仍面临着数据不足、姿态偏转、身份差异以及面部遮挡等难题。而随着生成对抗网络近年来在图像合成等方面成功,越来越多研究者将生成对抗网络应用在人脸表情识别技术中,并取得了显著的效果。 有鉴于此,首先将对生成对抗网络原理进行介绍,然后从解决数据不足、姿态偏差、身份差异以及面部遮挡四个方面,对近年来生成对抗网络在人脸表情识别技术的研究进行分析和总结,最后展望生成对抗网络在人脸表情识别技术中的前景和发展方向。
Abstract:
Facial expression recognition has been widely used in the fields of human-computer interaction,intelligent control,security and psychology,and the development of deep learning has made great progress in facial expression recognition technology. However,the faceexpression recognition technology still faces the problems of insufficient data,pose-invariant,identity-invariant and occlusion affects. Inrecent years,with the success in image synthesis,more and more researchers have applied the generative adversarial network to facial ex鄄pression recognition technology and achieved remarkable results. In view of this,firstly,we will introduce the principle of generative ad鄄versarial network, and then analyze and summarize the research of generative adversarial network in facial expression recognition technology in recent years form four aspects of solving data shortage,pose-invariant,identity-invariant and facial occlusion. Finally,we look forward to the prospect and development direction of generative adversarial network in facial expression recognition technology.

相似文献/References:

[1]王海东 朱文华 苏玉鹏.基于3DMouse的虚拟仿真系统人机交互技术[J].计算机技术与发展,2009,(10):18.
　WANG Hai-dong,ZHU Wen-hua,SU Yu-peng.The Human - Computer Interaction Technology of Virtual Simulation System Based on 3DMouse[J].,2009,(增刊):18.
[2]孙丽娟 张立材 郭彩龙.基于视觉的手势识别技术[J].计算机技术与发展,2008,(10):214.
　SUN Li-juan,ZHANG Li-cai,GUO Cai-long.Technologies of Hand Gesture Recognition Based on Vision[J].,2008,(增刊):214.
[3]张立臣 毛庆 冯德民 王映辉.一种用户目标驱动的交互设计方法[J].计算机技术与发展,2006,(01):193.
　ZHANG Li-ehen,MAO Qing,FENG De-min,et al.An Approach of User-Target Driven Interaction Design[J].,2006,(增刊):193.
[4]汪小寒 项响琴[] 陈洁 张燕平.基于PowerBuilder的运费编辑器的设计与实现[J].计算机技术与发展,2006,(04):135.
　WANG Xiao-han,XIANG Xiang-qin,CHEN Jie,et al.Design and Implementation of Freight Editor Based on PowerBuilder[J].,2006,(增刊):135.
[5]谢亮,廖宏建,杨玉宝.基于Kinect的姿势识别与应用研究[J].计算机技术与发展,2013,(05):258.
　XIE Liang,LIAO Hong-jian,YANG Yu-bao.Recognition and Application Research of Kinect-based Gesture[J].,2013,(增刊):258.
[6]刘维学,郑丽娟.一种软件人机界面设计综合评价方法[J].计算机技术与发展,2014,24(04):114.
　LIU Wei-xue[],ZHENG Li-juan[].A Comprehensive Evaluation Method of Human-computer Interface Design[J].,2014,24(增刊):114.
[7]陈燕军,汪地,杨浩,等. 基于Kinect的手术辅助系统研究[J].计算机技术与发展,2014,24(09):81.
　CHEN Yan-jun,WANG Di,YANG Hao,et al. Research on Operation Auxiliary System Based on Kinect[J].,2014,24(增刊):81.
[8]潘峥嵘,贺秀伟.人脸表情识别在智能机器人中的应用研究[J].计算机技术与发展,2018,28(02):173.[doi:10．3969/j．issn．1673－629X．2018．02．037]
　PAN Zheng-rong,HE Xiu-wei.Research on Application of Facial Expression Ｒecognition in Intelligent Ｒobot[J].,2018,28(增刊):173.[doi:10．3969/j．issn．1673－629X．2018．02．037]
[9]罗章[][][],谭海波[][],李晓风[][][],等. Kinect运动捕获技术在健康医疗中的应用研究[J].计算机技术与发展,2016,26(08):104.
　LUO Zhang[][][],TAN Hai-bo[][],LI Xiao-feng[][][],et al. Research on Application of Kinect Motion Capture Technology in Health Care[J].,2016,26(增刊):104.
[10]薛佳[][][],栗觅[][][],马理旺[][][],等. 基于视觉行为的网上用户识别[J].计算机技术与发展,2017,27(02):11.
　XUE Jia[][][],LI Mi[][][],MA Li-wang[][][],et al. Online User Identification Based on Visual Behaviors[J].,2017,27(增刊):11.
[11]崔凤焦.表情识别算法研究进展与性能比较[J].计算机技术与发展,2018,28(02):145.[doi:10．3969/j．issn．1673－629X．2018．02．031]
　CUI Feng-jiao.Ｒesearch and Performance Comparison of Facial Expression Ｒecognition Algorithm[J].,2018,28(增刊):145.[doi:10．3969/j．issn．1673－629X．2018．02．031]

更新日期/Last Update: 2021-09-10