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

机译:如何使机器人微笑?从数字化提取的面部地标配置中感知情感表达

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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:为了设计能够准确显示表明情绪状态的面部表情的机器人或具体化的对话代理,我们需要产生这些面部表情的技术,并且需要研究这些技术与人类对这些人造面部的社会感知之间的关系的研究。我们的出发点是评估人类对核心面部信息的感知:代表面部标志的移动点,即面部关键部位的位置和运动。较早的研究表明,当参与者看到的真实人类全脸都是移动的代表面部标志的白色画点时,他们可以相对准确地识别面部表情(尽管不如识别全脸那样准确)。在当前的研究中,我们调查了可比的面部标志物识别出的情绪的准确性(与全脸表达的情绪识别出的准确性相比),但是现在使用面部跟踪软件来生成面部标志物。与早期的研究结果一致,研究结果表明,参与者可以准确地识别面部标志所表达的情绪(尽管不如全脸所表达的准确)。因此,这些结果为进一步研究产生面部情感表情的技术(AI方法)的基本特征及其由人类使用者进行评估提供了起点。

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