IntraFace。

Fernando De la Torre, Wen-Sheng Chu, Xuehan Xiong, Francisco Vicente, Xiaoyu Ding, Jeffrey Cohn
{"title":"IntraFace。","authors":"Fernando De la Torre, Wen-Sheng Chu, Xuehan Xiong, Francisco Vicente, Xiaoyu Ding, Jeffrey Cohn","doi":"10.1109/FG.2015.7163082","DOIUrl":null,"url":null,"abstract":"<p><p>Within the last 20 years, there has been an increasing interest in the computer vision community in automated facial image analysis algorithms. This has been driven by applications in animation, market research, autonomous-driving, surveillance, and facial editing among others. To date, there exist several commercial packages for specific facial image analysis tasks such as facial expression recognition, facial attribute analysis or face tracking. However, free and easy-to-use software that incorporates all these functionalities is unavailable. This paper presents IntraFace (IF), a publicly-available software package for automated facial feature tracking, head pose estimation, facial attribute recognition, and facial expression analysis from video. In addition, IFincludes a newly develop technique for unsupervised synchrony detection to discover correlated facial behavior between two or more persons, a relatively unexplored problem in facial image analysis. In tests, IF achieved state-of-the-art results for emotion expression and action unit detection in three databases, FERA, CK+ and RU-FACS; measured audience reaction to a talk given by one of the authors; and discovered synchrony for smiling in videos of parent-infant interaction. IF is free of charge for academic use at http://www.humansensing.cs.cmu.edu/intraface/.</p>","PeriodicalId":91494,"journal":{"name":"IEEE International Conference on Automatic Face & Gesture Recognition and Workshops","volume":"1 ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2015-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4918819/pdf/nihms-751967.pdf","citationCount":"0","resultStr":"{\"title\":\"IntraFace.\",\"authors\":\"Fernando De la Torre, Wen-Sheng Chu, Xuehan Xiong, Francisco Vicente, Xiaoyu Ding, Jeffrey Cohn\",\"doi\":\"10.1109/FG.2015.7163082\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Within the last 20 years, there has been an increasing interest in the computer vision community in automated facial image analysis algorithms. This has been driven by applications in animation, market research, autonomous-driving, surveillance, and facial editing among others. To date, there exist several commercial packages for specific facial image analysis tasks such as facial expression recognition, facial attribute analysis or face tracking. However, free and easy-to-use software that incorporates all these functionalities is unavailable. This paper presents IntraFace (IF), a publicly-available software package for automated facial feature tracking, head pose estimation, facial attribute recognition, and facial expression analysis from video. In addition, IFincludes a newly develop technique for unsupervised synchrony detection to discover correlated facial behavior between two or more persons, a relatively unexplored problem in facial image analysis. In tests, IF achieved state-of-the-art results for emotion expression and action unit detection in three databases, FERA, CK+ and RU-FACS; measured audience reaction to a talk given by one of the authors; and discovered synchrony for smiling in videos of parent-infant interaction. IF is free of charge for academic use at http://www.humansensing.cs.cmu.edu/intraface/.</p>\",\"PeriodicalId\":91494,\"journal\":{\"name\":\"IEEE International Conference on Automatic Face & Gesture Recognition and Workshops\",\"volume\":\"1 \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4918819/pdf/nihms-751967.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE International Conference on Automatic Face & Gesture Recognition and Workshops\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FG.2015.7163082\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE International Conference on Automatic Face & Gesture Recognition and Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FG.2015.7163082","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

在过去 20 年里,计算机视觉领域对自动面部图像分析算法的兴趣与日俱增。这主要是受动画、市场研究、自动驾驶、监控和面部编辑等应用的推动。迄今为止,已有几种商业软件包可用于特定的面部图像分析任务,如面部表情识别、面部属性分析或面部跟踪。然而,整合了所有这些功能的免费且易于使用的软件却还没有。本文介绍的 IntraFace(IF)是一款可公开获取的软件包,用于自动面部特征跟踪、头部姿态估计、面部属性识别和视频面部表情分析。此外,IF 还包括一项新开发的无监督同步检测技术,用于发现两人或多人之间相关的面部行为,这是面部图像分析中一个相对尚未开发的问题。在测试中,IF 在三个数据库(FERA、CK+ 和 RU-FACS)中的情绪表达和动作单元检测方面取得了最先进的结果;测量了听众对作者之一演讲的反应;发现了亲子互动视频中微笑的同步性。IF免费供学术界使用,http://www.humansensing.cs.cmu.edu/intraface/。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

摘要图片

摘要图片

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
IntraFace.

Within the last 20 years, there has been an increasing interest in the computer vision community in automated facial image analysis algorithms. This has been driven by applications in animation, market research, autonomous-driving, surveillance, and facial editing among others. To date, there exist several commercial packages for specific facial image analysis tasks such as facial expression recognition, facial attribute analysis or face tracking. However, free and easy-to-use software that incorporates all these functionalities is unavailable. This paper presents IntraFace (IF), a publicly-available software package for automated facial feature tracking, head pose estimation, facial attribute recognition, and facial expression analysis from video. In addition, IFincludes a newly develop technique for unsupervised synchrony detection to discover correlated facial behavior between two or more persons, a relatively unexplored problem in facial image analysis. In tests, IF achieved state-of-the-art results for emotion expression and action unit detection in three databases, FERA, CK+ and RU-FACS; measured audience reaction to a talk given by one of the authors; and discovered synchrony for smiling in videos of parent-infant interaction. IF is free of charge for academic use at http://www.humansensing.cs.cmu.edu/intraface/.

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
16th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2021, Jodhpur, India, December 15-18, 2021 Message from the General and Program Chairs FG 2020 Proof-Theoretic Aspects of Hybrid Type-Logical Grammars Undecidability of a Newly Proposed Calculus for CatLog3 On the Computational Complexity of Head Movement and Affix Hopping
×
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