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 are still unclear. Therefore, three experiments were conducted in this study to systematically explore a 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 features presented. The 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 show 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 the recognition of happiness, and the eyebrows were sufficient and necessary for the recognition of sadness. This study helps to clarify the perception mechanism underlying emotion recognition in cartoon faces and sheds some light on directions for future research on intelligent human-computer interactions.
Highlights
As an attractive art form, cartoon faces are widely used in daily life
The results of a simple effects analysis showed that the perceived intensity of the happy expression was higher for the real faces than for the cartoon faces (p < 0.001), while the perceived intensity of the sad expression was higher for the cartoon faces than for the real faces (p < 0.001)
The results show that the processing of emotion in cartoon faces share a similarity with the emotion processing mechanism in real faces, as the happy expression is identified more accurately than the neutral and sad expressions
Summary
As an attractive art form, cartoon faces are widely used in daily life. Cartoon animation is an important carrier that helps children acquire emotional knowledge (Baron-Cohen et al, 2009; Schlosser et al, 2019) but enables adults to express feelings and attitudes (Jonassaint et al, 2018). In the field of artificial intelligence and human-robot interaction research, there has been an urgent demand to incorporate emotional and sociable cartoon characters into the development of intelligent robots and virtual agents (Azevedo et al, 2019; Jaiswal et al, 2020). These nonrealistic agents with emotionally expressive, human-like cartoon faces will be treated as partners. A better understanding of emotional facial expression recognition in cartoon faces would provide a theoretical reference for humanintelligence interaction and emotional information for the development of emotionally expressive cartoon characters for artificial intelligence and sociable robot applications
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