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Facial Feature Movements Caused by Various Emotions: Differences According to Sex

机译:各种情绪引起的面部特征运动:性别差异

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Facial muscle micro movements for eight emotions were induced via visual and auditory stimuli and were verified according to sex. Thirty-one main facial features were chosen from the Kinect API out of 121 initially obtained facial features; the average change of pixel value was measured after image alignment. The proposed method is advantageous as it allows for comparisons. Facial micro-expressions are analyzed in real time using 31 facial feature points. The amount of micro-expressions for the various emotion stimuli was comparatively analyzed for differences according to sex. Men’s facial movements were similar for each emotion, whereas women’s facial movements were different for each emotion. The six feature positions were significantly different according to sex; in particular, the inner eyebrow of the right eye had a confidence level of p < 0.01. Consequently, discriminative power showed that men’s ability to separate one emotion from the others was lower compared to women’s ability in terms of facial expression, despite men’s average movements being higher compared to women’s. Additionally, the asymmetric phenomena around the left eye region of women appeared more strongly in cases of positive emotions.
机译:通过视觉和听觉刺激诱发八种情绪的面部肌肉微动,并根据性别进行验证。从Kinect API中从最初获得的121个面部特征中选择了31个主要面部特征。图像对准后,测量像素值的平均变化。所提出的方法是有利的,因为它允许进行比较。使用31个面部特征点实时分析面部微表情。比较分析了各种情绪刺激的微表情量,以根据性别进行差异分析。男人的脸部动作对于每种情感都是相似的,而女人的脸部动作对于每种情感都是不同的。六个特征位置因性别而异;特别是右眼内眉的置信度为p <0.01。因此,判别力表明,尽管男人的平均动作要比女人的平均动作要高,但男人在面部表情方面的能力要比女人的能力低。此外,在积极情绪的情况下,女性左眼周围的不对称现象更加明显。

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