面部表情识别:方法、性能和局限性的综述

Olufisayo S. Ekundayo, Serestina Viriri
{"title":"面部表情识别:方法、性能和局限性的综述","authors":"Olufisayo S. Ekundayo, Serestina Viriri","doi":"10.1109/ICTAS.2019.8703619","DOIUrl":null,"url":null,"abstract":"Facial expression is one of the profound nonverbal channels through which human emotion state is communicated, its automation involves analysis and recognition of facial features. Facial Expression Recognition (FER) is categorized as behavioral biometrics, and also applicable in the field of computer vision and human computer interaction. Variations in the nature of the images to be processed; head pose, image background, light intensity and occlusion are some of the sources of the challenges with facial expression recognition system. Achieving a robust automatic facial expression recognition system invariant to the aforementioned challenges, is the goal of this research area. This paper presents an analysis of major feature extraction and classification methods, their performances in terms of accuracy and their respective limitations.","PeriodicalId":386209,"journal":{"name":"2019 Conference on Information Communications Technology and Society (ICTAS)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"Facial Expression Recognition: A Review of Methods, Performances and Limitations\",\"authors\":\"Olufisayo S. Ekundayo, Serestina Viriri\",\"doi\":\"10.1109/ICTAS.2019.8703619\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Facial expression is one of the profound nonverbal channels through which human emotion state is communicated, its automation involves analysis and recognition of facial features. Facial Expression Recognition (FER) is categorized as behavioral biometrics, and also applicable in the field of computer vision and human computer interaction. Variations in the nature of the images to be processed; head pose, image background, light intensity and occlusion are some of the sources of the challenges with facial expression recognition system. Achieving a robust automatic facial expression recognition system invariant to the aforementioned challenges, is the goal of this research area. This paper presents an analysis of major feature extraction and classification methods, their performances in terms of accuracy and their respective limitations.\",\"PeriodicalId\":386209,\"journal\":{\"name\":\"2019 Conference on Information Communications Technology and Society (ICTAS)\",\"volume\":\"101 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-03-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 Conference on Information Communications Technology and Society (ICTAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICTAS.2019.8703619\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Conference on Information Communications Technology and Society (ICTAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICTAS.2019.8703619","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17

摘要

面部表情是人类情感状态交流的深层非语言渠道之一,其自动化涉及对面部特征的分析和识别。面部表情识别(FER)是一种行为生物识别技术,在计算机视觉和人机交互领域也有广泛的应用。待处理图像性质的变化;头部姿态、图像背景、光线强度和遮挡是人脸表情识别系统面临的挑战。实现一个鲁棒的面部表情自动识别系统是本研究领域的目标。本文分析了主要的特征提取和分类方法,以及它们在准确率方面的表现和各自的局限性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Facial Expression Recognition: A Review of Methods, Performances and Limitations
Facial expression is one of the profound nonverbal channels through which human emotion state is communicated, its automation involves analysis and recognition of facial features. Facial Expression Recognition (FER) is categorized as behavioral biometrics, and also applicable in the field of computer vision and human computer interaction. Variations in the nature of the images to be processed; head pose, image background, light intensity and occlusion are some of the sources of the challenges with facial expression recognition system. Achieving a robust automatic facial expression recognition system invariant to the aforementioned challenges, is the goal of this research area. This paper presents an analysis of major feature extraction and classification methods, their performances in terms of accuracy and their respective limitations.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A Review of Local, Holistic and Deep Learning Approaches in Facial Expressions Recognition Facial Expression Recognition: A Review of Methods, Performances and Limitations Analysis of the Narrow Band Internet of Things (NB-IoT) Technology A Twitter knowledge sharing model based on small businesses in the Western Cape An SDN Solution for Performance Improvement in Dedicated Wide-Area Networks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1