The judgement of facial beauty was influenced by many factors. In current study, we investigated how the image statistics (including slope of amplitude spectrum and symmetry index) and perceived symmetry influenced facial attractiveness. 228 faces were normalized to the same rms contrast and modified to produce its symmetrical face and asymmetrical face by morphing technique. The task of the observers was to rate each face for its attractiveness, perceived symmetry, valence and arousal in the emotion dimension. In Experiment 1, we used symmetrical and asymmetrical faces as stimuli. Our results showed that the symmetrical face has higher values of symmetry index and slope, and was rated as more attractive, symmetrical and with higher positive emotion. Furthermore, the facial attractiveness could be predicted by symmetry index, slope, perceived symmetric and emotional valence by linear regression. In Experiment 2, we used original faces and asked other participants to do the same task. The results were similar to Experiment 1. The attractiveness rating for randomly chosen faces could be also predicted by the rest of the faces by using the same parameter weights in linear regression. We also adapted path analysis to investigate how the physical properties (symmetry index and slope) influences participants' attractiveness rating via perceived symmetry and emotion judgement. Our results suggested the beauty of the faces was contributed by the image statistics, perceived symmetry and valence of the emotion.
|Translated title of the contribution||The Perception of Facial Beauty: The Contribution of Image Statistics and Perceived Symmetry|
|Original language||Chinese (Traditional)|
|Journal||中華心理學刊 ＝ Chinese Journal of Psychology|
|Publication status||Published - 2020 Sep 1|