Abstract
The goal is to create a virtual character that has a human-like personality and that can emotionally respond while conversing with a user. To this end, some researchers mathematically model emotions, behavior, mood, and personality for virtual characters. As we describe here, researchers can use these models to create an emotionally responsive character. However, such models lack the critical component of memory - a memory of not just events but also past emotional interaction. We’ve developed a memory-based emotion model that uses the memory of past interactions to build long-term relationships between the virtual character and users. We combine this model with state-of-the-art animation blending to generate smooth animation for the character during the interaction. To make the interaction more natural, we also use face recognition techniques; the character can thus remember a user’s face and automatically adjust the current interaction on the basis of its existing relationship with the user. Finally, to increase the user’s immersion, we place a life-sized character in a real environment using marker-based augmented reality (AR) techniques. Our example application is Eva, a geography teacher who has multiple interactions with two student users.