考虑面部表情和生理信号的情绪识别

Chuan-Yu Chang, Jeng-Shiun Tsai, Chi-Jane Wang, P. Chung
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引用次数: 50

摘要

提出了一种综合考虑面部表情和生理信号的情绪识别系统。通过特定设计的情绪诱导实验,采集被试的面部表情图像和生理信号。从面部表情图像中检测出14个特征点,提取出12个面部特征。同时,我们测量受试者的皮肤电导率,手指温度和心率。同时采用面部特征和生理特征来训练分类器。采用两个学习向量量化(LVQ)神经网络对爱、喜、喜、恐四种情绪进行分类。实验结果表明,该识别系统能够通过面部表情、生理信号以及两者同时识别四种情绪。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Emotion recognition with consideration of facial expression and physiological signals
An emotion recognition system with consideration of facial expression and physiological signals is proposed in this paper. A specific designed mood induction experiment is performed to collect facial expressing images and physiological signals of subjects. We detected 14 feature points and extracted 12 facial features from facial expression images. Meanwhile, we measure the skin conductivity, finger temperature and heart rate from the subject. Both facial and physiological features are adopted to train the classifiers. Two learning vector quantization (LVQ) neural networks were applied to classify four emotions: love, joy, surprise and fear. Experimental results show the proposed recognition system is able to identify four emotions by facial expressions, physiological signals, and both of them.
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