MULTIMODAL SYSTEM FOR FACIAL EMOTION RECOGNITION BASED ON DEEP LEARNING

Q3 Engineering
Atanas V. Atanassov, D. Pilev, F. Tomova
{"title":"MULTIMODAL SYSTEM FOR FACIAL EMOTION RECOGNITION BASED ON DEEP LEARNING","authors":"Atanas V. Atanassov, D. Pilev, F. Tomova","doi":"10.59957/jctm.v59.i3.2024.29","DOIUrl":null,"url":null,"abstract":"Emotions are one of the main ways of communication between people and of expressing attitudes towards objects, products, services, etc. They are divided to verbal and non-verbal classes. Human speech and intonation belong to the first class, and to the second (non-verbal) facial and body emotions, known as body language. The subject of this report is the development of multimodal deep learning system intended to recognize facial and body emotions and their relationship with the scene (weather) in which they occur. It is based on three deep learning neural networks (DNN) each one for recognition of facial emotion, body emotion and weather. Combining their results, we improve significantly the final facial emotion recognition (FER) results.","PeriodicalId":38363,"journal":{"name":"Journal of Chemical Technology and Metallurgy","volume":"13 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Chemical Technology and Metallurgy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.59957/jctm.v59.i3.2024.29","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 0

Abstract

Emotions are one of the main ways of communication between people and of expressing attitudes towards objects, products, services, etc. They are divided to verbal and non-verbal classes. Human speech and intonation belong to the first class, and to the second (non-verbal) facial and body emotions, known as body language. The subject of this report is the development of multimodal deep learning system intended to recognize facial and body emotions and their relationship with the scene (weather) in which they occur. It is based on three deep learning neural networks (DNN) each one for recognition of facial emotion, body emotion and weather. Combining their results, we improve significantly the final facial emotion recognition (FER) results.
基于深度学习的面部情绪识别多模态系统
情感是人与人之间交流以及表达对物品、产品、服务等态度的主要方式之一。情绪分为语言和非语言两类。人类的语言和语调属于第一类,面部和肢体情绪属于第二类(非语言),即肢体语言。本报告的主题是开发多模态深度学习系统,旨在识别面部和肢体情绪及其与发生场景(天气)的关系。该系统基于三个深度学习神经网络(DNN),分别用于识别面部情绪、肢体情绪和天气。将它们的结果结合起来,我们就能显著改善最终的面部情绪识别(FER)结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Journal of Chemical Technology and Metallurgy
Journal of Chemical Technology and Metallurgy Engineering-Industrial and Manufacturing Engineering
CiteScore
1.40
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信