This paper presents an affective model that determines the emotional state of a character according to the personality traits and the experienced emotions. We consider an emotional state as the layer between personality and emotion. The proposed affective model offers a mapping between emotions and emotional states. To evidence emotional states of a virtual character, we can attribute them facial expressions based on their associated emotions. Facial expressions for intermediate emotions are generated automatically from expressions for universal emotions. The experiments show coherent emotional states produced by a simulated story. They also present how the corresponding emotions were represented through dynamic and static facial expressions. Finally, the obtained results demonstrate the satisfactory recognition by a group of people unfamiliar with the work described. Copyright

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The project Stylized Animations for Research on Autism (SARA) aims to develop a better understanding of the cognitive processes behind emotional categorization in children and adolescents with high-functioning autism spectrum disorder (ASD), in comparison with neurotypically developed peers. To this end, we combine novel realtime non-photorealistic rendering (NPR) algorithms, emotional facial animations, and eye-tracking technologies in a framework that serves as an interactive testbed for empirical research. In this paper, we focus on three experiments that: (1) validate real-time facial animations of virtual characters, (2) evaluate the NPR algorithms to create abstracted facial expressions, and (3) elucidate the relation between eye gaze behavior, ASD and alexithymia (i.e., difficulties in expressing ones emotions). The results show that our animations can be used in the proposed experiments; however, more evaluation is needed regarding the NPR abstractions, especially with individuals with ASD. Finally, even though no correlation was found between gaze behavior, ASD and alexithymia, the study opened several questions that will be addressed in future work.

This paper presents the motivation, background and implementation of The Muses of Poetry, an interactive installation that combines dynamically generated character animation, semantic analysis, natural voice interaction and affect in poetry. Inspired by the subjectivity and ethereal quality of this literary art, we wanted to enhance the act of reciting poetry by providing a set of characters the possibility to "understand" and manifest the emotional content of the poems through facial expressions and affective speech. We believe that this original installation will bring poetry closer to a wider audience, while creating a playful, interactive and surprising experience for the user.

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