AUTHOR=Zhang Shu , Liu Xinge , Yang Xuan , Shu Yezhi , Liu Niqi , Zhang Dan , Liu Yong-Jin 

TITLE=The Influence of Key Facial Features on Recognition of Emotion in Cartoon Faces

JOURNAL=Frontiers in Psychology

VOLUME=Volume 12 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2021.687974

DOI=10.3389/fpsyg.2021.687974

ISSN=1664-1078

ABSTRACT=Cartoon faces are widely used in social media, animation production, and social robots because of their attractive ability to convey different emotional information. Despite their popular applications, the mechanisms of recognizing emotional expressions in cartoon faces is still unclear. Therefore, three experiments were conducted in the current study to systematically explore recognition process for emotional cartoon expressions (happy, sad, and neutral) and to examine the influence of key facial features (mouth, eyes, and eyebrows) on emotion recognition. Across the experiments, three presentation conditions were employed: (1) a full face; (2) individual feature only (with two other features concealed); and (3) one feature concealed with two other presented. Cartoon face images used in this study were converted from a set of real faces acted by Chinese posers and the observers were Chinese. The results showed that happy cartoon expressions were recognized more accurately than neutral and sad expressions, which was consistent with the happiness recognition advantage revealed in real face studies. Compared with real facial expressions, sad cartoon expressions were perceived as sadder, and happy cartoon expressions were perceived as less happy, regardless of whether full-face or single facial features were viewed. For cartoon faces, the mouth was demonstrated to be a feature that is sufficient and necessary for happiness recognition, and the eyebrows were sufficient and necessary for sadness recognition. The current study helps to clarify the perception mechanism underlying the emotion recognition in cartoon faces and sheds some light on directions for future research on intelligent human-computer interactions.