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How to Make a Robot Smile? Perception of Emotional Expressions from Digitally-Extracted Facial Landmark Configurations

机译:如何让机器人微笑?从数字提取的面部地标配置的情绪表达的感知

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To design robots or embodied conversational agents that can accurately display facial expressions indicating an emotional state, we need technology to produce those facial expressions, and research that investigates the relationship between those technologies and human social perception of those artificial faces. Our starting point is assessing human perception of core facial information: Moving dots representing the facial landmarks, i.e., the locations and movements of the crucial parts of a face. Earlier research suggested that participants can relatively accurately identity facial expressions when all they can see of a real human full face are moving white painted dots representing the facial landmarks (although less accurate than recognizing full faces). In the current study we investigated the accuracy of recognition of emotions expressed by comparable facial landmarks (compared to accuracy of recognition of emotions expressed by full faces), but now used face-tracking software to produce the facial landmarks. In line with earlier findings, results suggested that participants could accurately identify emotions expressed by the facial landmarks (though less accurately than those expressed by full faces). Thereby, these results provide a starting point for further research on the fundamental characteristics of technology (AI methods) producing facial emotional expressions and their evaluation by human users.
机译:为了设计机器人或体现,能精确显示的面部表情指示情绪状态会话代理,我们需要的技术生产的面部表情,和研究调查这些技术和那些人造脸的人的社会知觉之间的关系。我们的出发点是评价的核心脸部信息人类感知:移动的小圆点代表面部界标,即面部的关键部件的位置和运动。此前的研究表明,参与者可以比较,当所有他们可以看到一个真正的人满脸正在代表脸部标志(虽然不承认全脸不太准确)漆成白色的点准确地识别面部表情。在目前的研究中,我们调查了认可可比脸部显着标记表达情感的准确度(相对于认可全脸表达情感的准确度),但现在使用脸部追踪软件来产生面部界标。在与早期发现一致,结果表明,参与者可以准确地识别由脸部标志表达情绪(尽管比那些全脸表示不太准确)。因此,这些结果提供了有关生产面部表情表情和人类用户的评价技术的基本特点(AI方法)进一步研究的出发点。

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