FaceTube: predicting personality from facial expressions of emotion in online conversational video
FaceTube: predicting personality from facial expressions of emotion in online conversational video
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FaceTube：根据在线对话视频中情绪的面部表情来预测性格
DOI：
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
D. Gática
中科院分区：
文献类型：
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作者：
Joan;L. Teijeiro;D. Gática
人脸表情自动识别技术的发展使得大量数据的挖掘和表征成为可能，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描述一种流行的在线社交视频，会话视频博客的用户。首先，我们提出使用几个活动线索来表征vlogger基于情绪面部表情的逐帧估计。然后，我们展示了使用面部表情和五大特征自动预测vlogger的个性印象的任务的结果。我们的研究结果是有希望的，特别是对于外倾印象的情况下，此外，我们的工作提出了有趣的问题，关于多个自然的面部表情发生在会话视频的表示。
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.