从距离数据到基于解剖的动画人脸:一种模型适应方法

Yu Zhang, T. Sim, C. Tan
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引用次数: 6

摘要

本文提出了一种新的方法,以最小的人工干预,从距离数据重建动画,基于解剖的个人面部模型。一个具有多层皮肤-肌肉-颅骨结构的原型模型作为我们方法的起点。经过全局自适应后,将原型模型的蒙皮网格表示为动态可变形模型,该模型根据表面弹性特性产生的内力和扫描数据点和特征产生的外力进行变形以拟合扫描数据。由三种类型的面部肌肉组成的底层肌肉层会自动适应。根据适应的皮肤和肌肉结构,对一组自动生成的颅骨特征点进行变换,驱动颅骨模板模型的体积变形,进行颅骨拟合。重建的模型逼真地再现了一个特定的人的形状和特征,并可以即时动画。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
From range data to animated anatomy-based faces: a model adaptation method
This paper presents a new method for reconstructing animated, anatomy-based facial models of individuals from range data with minimal manual intervention. A prototype model with a multi-layer skin-muscle-skull structure serves as the starting point for our method. After the global adaptation, the skin mesh of the prototype model is represented as a dynamic deformable model which is deformed to fit scanned data according to internal force stemming from the elastic properties of the surface and external forces produced from the scanned data points and features. The underlying muscle layer that consists of three types of facial muscles is automatically adapted. According to the adapted skin and muscle structures, a set of automatically generated skull feature points is transformed to drive a volume morphing of the template skull model for skull fitting. The reconstructed model realistically reproduces the shape and features of a specific person and can be animated instantly.
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