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Analyses of the Differences between Posed and Spontaneous Facial Expressions

机译:面部表情与自发表情的差异分析

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This paper presents comprehensive analyses of the differences between posed and spontaneous expressions from visible images. First, geometric and appearance features are extracted from the difference images between apex and onset facial images. Secondly, the differences between the posed and spontaneous facial expressions are analyzed through hypothetical testing methods from three aspects: on overall samples, on samples with different genders, and on samples with different expressions. Thirdly, Bayesian networks (BNs) are used to classify posed versus spontaneous expressions from the same three aspects. Statistical analyses on the NVIE database demonstrate the importance of the geometric and appearance features for discriminating posed and spontaneous expressions. Gender effect exists on the differences between posed and spontaneous expressions. It is easier to distinguish posed happiness from spontaneous happiness than other expressions. Recognition experimental results confirm the observations of statistical analyses in most cases.
机译:本文对可见图像中姿势和自发表情之间的差异进行了综合分析。首先,从顶点和面部面部图像之间的差异图像中提取几何特征和外观特征。其次,通过假设的测试方法,从三个方面对姿势和自发面部表情之间的差异进行了分析:整体样本,性别不同的样本以及表情不同的样本。第三,从相同的三个方面,使用贝叶斯网络(BN)对姿势和自发表达进行分类。 NVIE数据库上的统计分析表明,几何和外观特征对于区分姿势和自发表情的重要性。性别效应存在于自发表情与自发表情之间的差异上。与其他表达方式相比,将自发的幸福与自发的幸福区分开比较容易。公认的实验结果证实了大多数情况下的统计分析结果。

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