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Study of Recognizing Spontaneous Facial Expressions of a Person who Watches Web News Based on ASM and Bayesian Network

机译:基于ASM和贝叶斯网络的看网络新闻者自发表情的研究。

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摘要

To achieve a comment system that can automatically estimate emotions of a person who watches web news, this paper proposes a computer vision based method that can recognize facial expressions generated in response to Web news. During the learning session, first, ASM (Active Shape Model) is applied to the face so that some feature points are located. From the located feature points, some features such as distances between feature points are obtained. The features collected from sample data are used for nodes of Bayesian Networks. During facial expression estimation session, the features that are computed from the input facial video sequence by the same procedure as the learning session are input to the Bayesian Networks so that the recognition result is obtained as the facial expression category that maximizes the a-posteriori probability. Experimental results demonstrate the effectiveness of the proposed method.
机译:为了实现一种可以自动估计观看网络新闻的人的情绪的评论系统,本文提出了一种基于计算机视觉的方法,该方法可以识别响应网络新闻而生成的面部表情。在学习过程中,首先,将ASM(活动形状模型)应用于面部,以便定位一些特征点。从所定位的特征点获得一些特征,例如特征点之间的距离。从样本数据收集的特征用于贝叶斯网络的节点。在面部表情估计会话期间,将通过与学习会话相同的过程从输入的面部视频序列中计算出的特征输入贝叶斯网络,以便获得识别结果作为最大化后验概率的面部表情类别。实验结果证明了该方法的有效性。

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