Authentic facial expression analysis
Authentic facial expression analysis
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DOI：
10.1016/j.imavis.2005.12.021
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发表时间：
2007-12-03
影响因子：
4.7
通讯作者：
Huang, T. S.
中科院分区：
文献类型：
--
作者：
Sebe, N.;Lew, M. S.;Huang, T. S.
在人机交互范式中，情绪智能是一种日益增长的趋势。为了对人类做出适当的反应，计算机需要对人类的情绪状态有一些感知。我们断言，机器感知情绪的最大信息量渠道是通过视频中的面部表情。目前评估自动情绪检测的一个困难是，目前还没有基于真实情绪的国际数据库。目前的面部表情数据库包含的面部表情与受试者的情绪状态没有自然联系。我们在这项工作中的贡献有两个：首先，我们创建了第一个真实的面部表情数据库，测试对象根据他们的情绪状态展示自然的面部表情。其次，我们评估了几种有前景的机器学习情感检测算法，包括贝叶斯网络、支持向量机和决策树等技术。(C)2006爱思唯尔B.V.保留所有权利。
There is a growing trend toward emotional intelligence in human-computer interaction paradigms. In order to react appropriately to a human, the computer would need to have some perception of the emotional state of the human. We assert that the most informative channel for machine perception of emotions is through facial expressions in video. One current difficulty in evaluating automatic emotion detection is that there are currently no international databases which are based on authentic emotions. The current facial expression databases contain facial expressions which are not naturally linked to the emotional state of the test subject. Our contributions in this work are twofold: first, we create the first authentic facial expression database where the test subjects are showing the natural facial expressions based upon their emotional state. Second, we evaluate the several promising machine learning algorithms for emotion detection which include techniques such as Bayesian networks, SVMs, and decision trees. (C) 2006 Elsevier B.V. All rights reserved.