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User Mood Detection in a Social Network Messenger Based on Facial Cues

机译:基于面部提示的社交网络Messenger中的用户情绪检测

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In this paper, we propose a mood detection approach which is crucial for human-computer and human-human interaction. In the proposed method, the facial emotional changes are observed through a camera while users use a social network messenger. The advantage of this approach, over the previously proposed approaches, is in its natural setup in which people facially express their feelings, while they read and interact in the social network. This setup eliminates the need for artificial stimulus since social networks are normally filled with different stimulus. The proposed approach is implemented on the Telegram social media messenger. The results show good performance in determining the mood of users. A very promising usage of the proposed approach is in helping human-human relation by providing the mood of one person to another person before an encounter.
机译:在本文中,我们提出了一种情绪检测方法,这对于人计算机和人类互动至关重要。在所提出的方法中,通过相机观察面部情绪变化,而用户使用社交网络信使。这种方法的优势在以前提出的方法中,在其自然设置中,人们在社交网络中读取和互动时,人们会大大表达自己的感受。此设置消除了对人工刺激的需求,因为社交网络通常填充不同的刺激。提出的方法是在电报社交媒体信使上实施的。结果在确定用户的情绪方面表现出良好的性能。在遭遇前向另一个人提供一个人的情绪,拟议方法的非常有希望的使用是帮助人类的关系。

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