Learning-Based Techniques for Facial Animation
Loading...
Date
Authors
Aneja, Deepali
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
For decades, animation has been a popular storytelling technique. Traditional tools for creating animations are labor-intensive, requiring animators to painstakingly draw frames and motion curves by hand. An alternative workflow is to equip animators with direct real-time control over digital characters via performance, which offers a more immediate and efficient way to create animation. Even when using these existing expression transfer and lip sync methods, producing convincing facial animation in real-time is a challenging task. In this work, we present several deep learning techniques to model and automate the process of perceptually valid expression retargeting from humans to characters, real-time lip sync for animation, and building an emotionally aware embodied conversational agent. We also present the findings from user studies and some promising future directions in this domain.
Description
Thesis (Ph.D.)--University of Washington, 2019
Keywords
conversational style, deep learning, embodied conversational agent, expression retargeting, facial animation, lip sync, Computer science