Persona

Author:

Braun Adriana1,Queiroz Rossana1,Lee Wonsook2,Feijo Bruno3,Musse Soraia Raupp4

Affiliation:

1. Pontifical Catholic University of Rio Grande do Sul

2. University of Ottawa

3. Pontifical Catholic University of Rio de Janeiro

4. Pontifical Catholic University of Rio Grande do Sul, PUCRS - Porto Alegre, Brazil

Abstract

This article proposes the Persona method. The goal of the prosposed method is to learn and classify the facial actions of actors in video sequences. Persona is based on standard action units. We use a database with main expressions mapped and pre-classified that allows the automatic learning and faces selection. The learning stage uses Support Vector Machine (SVM) classifiers to identify expressions from a set of feature points tracked in the input video. After that, labeled control 3D masks are built for each selected action unit or expression, which composes the Persona structure. The proposed method is almost automatic (little intervention is needed) and does not require markers on the actor’s face or motion capture devices. Many applications are possible based on the Persona structure such as expression recognition, customized avatar deformation, and mood analysis, as discussed in this article.

Funder

Brazilian research agencies CAPES and CNPq

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Science Applications

Reference39 articles.

1. The Movement Advantage in Famous and Unfamiliar Faces: A Comparison of Point-Light Displays and Shape-Normalised Avatar Stimuli

2. Christopher M. Bishop. 2006. Pattern Recognition and Machine Learning. Springer-Verlag New York Inc. Secaucus NJ. Christopher M. Bishop. 2006. Pattern Recognition and Machine Learning. Springer-Verlag New York Inc. Secaucus NJ.

3. Selective Transfer Machine for Personalized Facial Action Unit Detection

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Investigating Emotion Style in Human Faces and Avatars;2019 18th Brazilian Symposium on Computer Games and Digital Entertainment (SBGames);2019-10

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3