Generating Emotionally Expressive Look-At Animation

摘要

Humanoid characters in video games are generally animated using motion capture technology, enabling high-quality, realistic animation. This animation has to remain interactive and allow characters to react to their environment; one important component of this adaptation are look-at animations which direct the character’s torso towards an object or person of interest. Look-at animations are generated procedurally in order to handle any desired target direction, however, this procedural animation can have a robotic quality and negatively affect the overall perceived realism of the character. In this work, we present a neural network controller for generating look-at animations that are equally as appealing as motion capture while requiring minimal memory. Moreover, our controller can generate animations stylized by emotion, allowing characters to react to look-at targets depending on their context, and this style expressiveness is shown to be on par with motion captured samples.