The Avatar’s Gist: How to Transfer Affective Components From Dynamic Walking to Static Body Postures - Presti, Paolo; Ruzzon, Davide; Galasso, Gaia Maria; Avanzini, Pietro; Caruana, Fausto; Vecchiato, Giovanni (Frontiers in Neuroscience, 2022)
Dynamic virtual representations of the human being can communicate a broad range of affective states through body movements, thus effectively studying emotion perception. However, the possibility of modeling static body postures preserving affective information is still fundamental in a broad spectrum of experimental settings exploring time-locked cognitive processes. Here, we propose a novel automatic method for creating virtual affective body postures starting from kinematics data. Exploiting body features related to postural cues and movement velocity, we transferred the affective components from dynamic walking to static body postures of male and female virtual avatars. Results of two online experiments showed that subjects coherently judged different valence and arousal levels in the avatar’s body posture, highlighting the reliability of the proposed methodology. In addition, aesthetic and postural cues made females more emotionally expressive than males. Overall, we provided a valid methodology to create affective body postures of virtual avatars, which can be used within different virtual scenarios to understand better the way we perceive the affective state of others.