RAS: A Data‐Driven Rigidity‐Aware Skinning Model For 3D Facial Animation,Computer Graphics Forum

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RAS: A Data‐Driven Rigidity‐Aware Skinning Model For 3D Facial Animation
Computer Graphics Forum ( IF 2.7 ) Pub Date : 2019-11-28 , DOI: 10.1111/cgf.13892
S‐L. Liu _{1,

2} , Y. Liu ₂ , L‐F. Dong ₁ , X. Tong _{1,

2}

Affiliation

We present a novel data‐driven skinning model—rigidity‐aware skinning (RAS) model, for simulating both active and passive 3D facial animation of different identities in real time. Our model builds upon a linear blend skinning (LBS) scheme, where the bone set and skinning weights are shared for diverse identities and learned from the data via a sparse and localized skinning decomposition algorithm. Our model characterizes the animated face into the active expression and the passive deformation: The former is represented by an LBS‐based multi‐linear model learned from the FaceWareHouse data set, and the latter is represented by a spatially varying as‐rigid‐as‐possible deformation applied to the LBS‐based multi‐linear model, whose rigidity parameters are learned from the data by a novel rigidity estimation algorithm. Our RAS model is not only generic and expressive for faithfully modelling medium‐scale facial deformation, but also compact and lightweight for generating vivid facial animation in real time. We validate the efficiency and effectiveness of our RAS model for real‐time 3D facial animation and expression editing.

中文翻译：

RAS：用于 3D 面部动画的数据驱动刚性感知蒙皮模型

我们提出了一种新的数据驱动的蒙皮模型——刚性感知蒙皮（RAS）模型，用于实时模拟不同身份的主动和被动 3D 面部动画。我们的模型建立在线性混合蒙皮 (LBS) 方案之上，其中骨骼集和蒙皮权重为不同的身份共享，并通过稀疏和局部蒙皮分解算法从数据中学习。我们的模型将动画人脸表征为主动表情和被动变形：前者由从 FaceWareHouse 数据集学习的基于 LBS 的多线性模型表示，后者由空间变化的、刚性的、应用于基于 LBS 的多线性模型的可能变形，其刚度参数是通过一种新颖的刚度估计算法从数据中学习的。我们的 RAS 模型不仅具有通用性和表现力，可以忠实地模拟中等规模的面部变形，而且小巧轻便，可以实时生成生动的面部动画。我们验证了 RAS 模型在实时 3D 面部动画和表情编辑方面的效率和有效性。

更新日期：2019-11-28

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