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A Method of Facial Animation Retargeting Based on Motion Capture

机译:基于运动捕捉的面部动画retarging方法方法

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By using facial motion data from passive optical motion capture system, this paper proposed an animation reconstruction approach, which is aimed to solve the common problem: model discontinuity and reconstructing a real-like facial animation. For this problem, a facial animation reconstruction approach with model divisions is proposed. We first divide facial model into different regions and request the deformed motion data by deploying RBF mapping. Then we adjust the deformed motion data to ensure their exactness. Besides, considering the nonlinear relationship of neighbors with the current point, we also proposed a facial animation reconstruction approach without model divisions, where we apply the motion of one-ring neighbors to adjust the deformed motion data. The experiments show that the proposed methods have an acceptable precision of reconstruction.
机译:通过使用来自无源光学运动捕获系统的面部运动数据,提出了一种动画重建方法,旨在解决常见问题:模型不连续性并重建真实的面部动画。对于这个问题,提出了一种具有模型分割的面部动画重建方法。我们首先将面部模型划分为不同的区域,并通过部署RBF映射来请求变形的运动数据。然后我们调整变形的运动数据以确保其精确性。此外,考虑到邻居与当前点的非线性关系,我们还提出了一种没有模型分割的面部动画重建方法,在那里我们应用单环邻居的运动来调整变形的运动数据。实验表明,该方法具有可接受的重建精度。

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