变换的线性组合

M. Alexa
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引用次数: 257

摘要

几何变换在计算机图形学中最常用方阵表示。在简单的几何论证之后,我们推导了一个自然的、几何上有意义的标量倍数的定义,以及基于矩阵表示的变换的交换加法,假设矩阵没有负的实特征值。总之,这些操作允许转换的线性组合。这提供了创建转换的加权组合、在转换之间进行插值以及在类似于向量空间的基的结构中构造或使用任意转换的能力。这些基本技术对于运动或动画的合成和分析非常有用。通过一组关键转换的动画是使用细分曲线等标准技术生成的。对于分析和渐进压缩,PCA可以应用于变换序列。我们描述了一个实现的技术,使易于使用和透明的方式处理图形软件中的几何变换。我们比较和联系我们的方法与其他技术,如矩阵分解和四元数插值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Linear combination of transformations
Geometric transformations are most commonly represented as square matrices in computer graphics. Following simple geometric arguments we derive a natural and geometrically meaningful definition of scalar multiples and a commutative addition of transformations based on the matrix representation, given that the matrices have no negative real eigenvalues. Together, these operations allow the linear combination of transformations. This provides the ability to create weighted combination of transformations, interpolate between transformations, and to construct or use arbitrary transformations in a structure similar to a basis of a vector space. These basic techniques are useful for synthesis and analysis of motions or animations. Animations through a set of key transformations are generated using standard techniques such as subdivision curves. For analysis and progressive compression a PCA can be applied to sequences of transformations. We describe an implementation of the techniques that enables an easy-to-use and transparent way of dealing with geometric transformations in graphics software. We compare and relate our approach to other techniques such as matrix decomposition and quaternion interpolation.
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