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Abstract

Companion technologies aim at developing sustained long-term relationships by employing emotional, nonverbal communication skills and empathy. One of the main challenges is to equip such companions with human-like abilities to reliably detect and analyze social signals. In this proposal, we focus our investigation on the modeling of visual processing mechanisms, since evidence in literature suggests that nonverbal interaction plays a key role in steering, controlling and maintaining social
interaction between humans. We seek to transfer fragments of this competence to the domain of human computer interaction. Some core computational mechanisms of
extracting and analyzing nonverbal signals are presented, enabling virtual agents to create socially competent response behaviors.