Abstract: 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.
Facial micro-expressions are analyzed in Reference REF using 31 facial points out of the 121 obtained using the Kinect face tracking API (Application Programming Interface).
Facial Feature Movements Caused by Various Emotions: Differences According to Sex
Symmetry
Symmetry
Computer Science Mathematics