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Radial Basis Functions Applied to Integral Interpolation, Piecewise Surface Reconstruction and Animation Control

机译:径向基函数应用于积分插值,分段曲面重构和动画控制

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摘要

This thesis describes theory and algorithms for use with Radial Basis Functions (RBFs), emphasising techniques motivated by three particular application areas.In Part I, we apply RBFs to the problem of interpolating to integral data. While the potential of using RBFs for this purpose has been established in an abstract theoretical context, their use has been lacking an easy to check sufficient condition for finding appropriate parent basic functions, and explicit methods for deriving integral basic functions from them. We present both these components here, as well as explicit formulations for line segments in two dimensions and balls in three and five dimensions. We also apply these results to real-world track data.In Part II, we apply Hermite and pointwise RBFs to the problem of surface reconstruction. RBFs are used for this purpose by representing the surface implicitly as the zero level set of a function in 3D space. We develop a multilevel piecewise technique based on scattered spherical subdomains, which requires the creation of algorithms for constructing sphere coverings with desirable properties and for blending smoothly between levels. The surface reconstruction method we develop scales very well to large datasets and is very amenable to parallelisation, while retaining global-approximation-like features such as hole filling. Our serial implementation can build an implicit surface representation which interpolates at over 42 million points in around 45 minutes.In Part III, we apply RBFs to the problem of animation control in the area of motion synthesis---controlling an animated character whose motion is entirely the result of simulated physics. While the simulation is quite well understood, controlling the character by means of forces produced by virtual actuators or muscles remains a very difficult challenge. Here, we investigate the possibility of speeding up the optimisation process underlying most animation control methods by approximating the physics simulator with RBFs.
机译:本文介绍了与径向基函数(RBF)一起使用的理论和算法,重点介绍了由三个特定应用领域所推动的技术。在第一部分中,我们将RBF应用于对整数数据进行插值的问题。虽然已经在抽象的理论背景下确定了将RBF用于此目的的潜力,但它们的使用却一直缺乏易于检查的足够条件来找到合适的父代基本功能,以及从中推导积分基本功能的明确方法。我们在此介绍了这两个组件,以及二维线段和三维和五维球的显式公式。我们还将这些结果应用于现实世界的轨道数据。在第二部分中,我们将Hermite和逐点RBF应用于表面重构问题。为此,通过将曲面隐式表示为3D空间中函数的零级集来使用RBF。我们开发了一种基于散布的球形子域的多级分段技术,该技术需要创建一些算法来构造具有所需属性的球面覆盖层,并在各个级别之间进行平滑融合。我们开发的表面重建方法非常适合大型数据集,并且非常适合并行化,同时保留诸如孔填充之类的近似全局特征。我们的串行实现可以构建隐式表面表示,在大约45分钟的时间内内插超过4,200万个点。在第三部分中,我们将RBF应用于运动合成领域中的动画控制问题-控制运动为完全是模拟物理学的结果。尽管已经很好地理解了模拟,但是通过虚拟执行器或肌肉产生的力来控制角色仍然是非常困难的挑战。在这里,我们研究了通过用RBF逼近物理模拟器来加快大多数动画控制方法基础的优化过程的可能性。

著录项

  • 作者

    Langton Michael Keith;

  • 作者单位
  • 年度 2009
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  • 原文格式 PDF
  • 正文语种 en
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