累进抽取模型的蒙皮

Xian Xiao, S. H. Soon, Feng Tian
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引用次数: 1

摘要

蒙皮现有的动画帧或例子被积极利用,以找到最合适的方案,能够捕获变形从给定的网格序列。有必要通过拟合算法来近似联合变换,这通常涉及求解大规模线性系统。在本文中,我们通过将示例网格表示为渐进抽取模型,大大降低了线性系统的维数。这些模型是由增强变形敏感抽取(ADSD)重建的,它能够处理大变形,同时在所有示例网格中保持连接关系。我们还展示了蒙皮可以传播到抽取模型,这使得动画可以扩展到具有不同质量要求的特定应用程序。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Skinning on Progressive Decimated Models
Skinning existing animation frames or examples is exploited actively to find the most suitable scheme that is capable of capturing deformations from given mesh sequences. It is necessary to approximate joint transformations by a fitting algorithm that usually involves solving a large scale linear system. In this paper, we reduce the dimensions of the linear system substantially by representing example meshes as progressive decimated models. These models are reconstructed from augmented deformation sensitive decimation (ADSD) that is able to handle large deformations while maintaining connectivity relationship throughout all example meshes. We also show that skinning can be propagated to decimated models, which allows animations to be scalable to specific applications with varied requirements of qualities.
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