Performance-based Expressive Character Animation

被引:0
|
作者
Aneja, Deepali [1 ]
机构
[1] Univ Washington, Paul G Allen Sch Comp Sci & Engn, Seattle, WA 98195 USA
关键词
Expression Retargeting; Lip Sync; Embodied Conversational Agents; Multi-modality; Deep Learning;
D O I
10.1145/3332167.3356880
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
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 position paper, I describe my past and proposed future research in developing interactive systems for perceptually-valid expression retargeting from humans to stylized characters, real-time lip sync for 2D animation, and building an expressive style aligned embodied conversational agent.
引用
收藏
页码:166 / 169
页数:4
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