Classification of Emotions from Video Based Cardiac Pulse Estimation
Classification of Emotions from Video Based Cardiac Pulse Estimation
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DOI：
10.1007/978-3-319-95957-3_33
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发表时间：
2018-08
期刊：
影响因子：
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通讯作者：
Keya Das;Antony Lam;Hisato Fukuda;Yoshinori Kobayashi;Y. Kuno
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文献类型：
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作者：
Keya Das;Antony Lam;Hisato Fukuda;Yoshinori Kobayashi;Y. Kuno
从视频中识别情感是一个非常活跃的研究课题，在人机交互、情感计算等领域有着广泛的应用。根据面部表情对情绪进行分类是一种常见的方法，但有时很难区分真实的情绪和虚假的情绪。在本文中，我们使用远程视频为基础的心脏活动传感技术，以获得生理数据，以识别情绪状态。我们表明，从遥感心脏脉搏模式单独，情绪状态可以区分。具体来说，我们进行了一项关于识别观看视频片段的人的情绪的实验研究。我们记录了26名受试者，他们都观看了相同的喜剧和恐怖视频片段，然后我们从视频片段中估计了他们的心脏脉搏信号。仅从心脏脉搏信号，我们就能够区分受试者是在观看喜剧还是恐怖视频剪辑。我们还使用面部动作单元对同一任务进行分类比较，并讨论这两种模式的比较情况。
Recognizing emotion from video is an active research theme with many applications such as human-computer interaction and affective computing. The classification of emotions from facial expression is a common approach but it is sometimes difficult to differentiate genuine emotions from faked emotions. In this paper, we use a remote video based cardiac activity sensing technique to obtain physiological data to identify emotional states. We show that from the remotely sensed cardiac pulse patterns alone, emotional states can be differentiated. Specifically, we conducted an experimental study on recognizing the emotions of people watching video clips. We recorded 26 subjects that all watched the same comedy and horror video clips and then we estimated their cardiac pulse signals from the video footage. From the cardiac pulse signal alone, we were able to classify whether the subjects were watching the comedy or horror video clip. We also compare against classifying for the same task using facial action units and discuss how the two modalities compare.