Analysis and synthesis of facial expressions with hand-generated muscle actuation basis
Analysis and synthesis of facial expressions with hand-generated muscle actuation basis
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基于手部肌肉驱动的面部表情分析与合成
DOI：
10.1109/ca.2001.982372
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发表时间：
2001
期刊：
影响因子：
--
通讯作者：
Hyeongseok Ko
中科院分区：
文献类型：
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作者：
Byoungwon Choe;Hyeongseok Ko
我们提出了一个性能驱动的面部动画系统，用于分析捕获的表情，找到肌肉驱动和合成的驱动值的表达。我们工作的一个显著不同的方法是，我们让艺术家雕刻驱动基础的初稿：与单个肌肉的孤立驱动相对应的基本面部形状，而不是完全依靠数学模型（如有限元方法）计算皮肤表面变形。我们通过基本元素的线性组合来合成表达式，并通过找到组合的权重来分析表达式。即使手动生成的驱动基础代表了主体的特征表达的本质，它也不够准确，不能用于随后的计算过程。我们还描述了一种迭代算法，以增加致动基础的精度。实验结果表明，我们的艺术家在循环的方法比纯数学模型产生更可预测和可控的结果，因此可以是一个非常有用的工具，在动画制作。
We present a performance-driven facial animation system for analyzing captured expressions to find muscle actuation and synthesizing expressions with the actuation values. A significantly different approach of our work is that we let artists sculpt the initial draft of the actuation basis: the basic facial shapes corresponding to the isolated actuation of individual muscles, instead of calculating skin surface deformation entirely, relying on mathematical models such as finite element methods. We synthesize expressions by linear combinations of the basis elements, and analyze expressions by finding the weights for the combinations. Even though the hand-generated actuation basis represents the essence of the subject's characteristic expressions, it is not accurate enough to be used in the subsequent computational procedures. We also describe an iterative algorithm to increase the accuracy of the actuation basis. The experimental results suggest that our artist-in-the-loop method produces a more predictable and controllable outcome than pure mathematical models, and thus can be a quite useful tool in animation productions.