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FaceTube: Predicting Personality from Facial Expressions of Emotion in Online Conversational Video

机译:FaceTube:通过在线对话视频中的情感表情预测人格

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The advances in automatic facial expression recognition make possible to mine and characterize large amounts of data, opening a wide research domain on behavioral understanding. In this paper, we leverage the use of a state-of-the-art facial expression recognition technology to characterize users of a popular type of online social video, conversational vlogs. First, we propose the use of several activity cues to characterize vloggers based on frame-by-frame estimates of facial expressions of emotion. Then, we present results for the task of automatically predicting vloggers' personality impressions using facial expressions and the Big-Five traits. Our results are promising, specially for the case of the Extraversion impression, and in addition our work poses interesting questions regarding the representation of multiple natural facial expressions occurring in conversational video.
机译:自动面部表情识别技术的进步使得挖掘和表征大量数据成为可能,从而为行为理解开辟了广阔的研究领域。在本文中,我们利用最先进的面部表情识别技术来表征流行类型的在线社交视频(对话视频博客)的用户。首先,我们建议使用几种活动线索来基于情绪面部表情的逐帧估计来表征vlogger。然后,我们提出使用面部表情和“五大”特征自动预测vlogger个性印象的任务的结果。我们的结果是有希望的,特别是对于Extraversion印象的情况,此外,我们的工作还提出了有关对话视频中出现的多种自然面部表情的表示形式的有趣问题。

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