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FEM-based scattered data modeling and visualization

机译:基于FEM的分散数据建模和可视化

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摘要

A critical challenge in visualizing scattered data is to correctly model the sample data so that data variation throughout the volume of interest can be accurately rendered. The commonly used interpolation-based approach is unsatisfactory, as it often generates physically impossible data values in the modeling process. In addition, it does not provide a systematic way of estimating errors. The interpolation methods used for modeling are usually different from those used for rendering, which causes inconsistency and misrepresentation. Furthermore, interpolation methods cannot handle discontinuities, due to their inherent assumption that the data are continuous. To eliminate these and other problems, we construct an alternative approach to scattered data visualization. Based on the finite element method (FEM), this FEM-based approach incorporates the governing equations of the data into the modeling process to ensure the modeled data to be physically meaningful. It provides error estimates that can guide the refinement of the finite element network to obtain the desired accuracy. It allows the selection of basis functions in the modeling process to match with the interpolation functions used by the rendering process so that consistency can be achieved. It handles discontinuities with the help of the double-layer scheme. Furthermore, it converts the data-modeling problem from an interpolation problem into a boundary-value problem, and therefore reduces the requirement on the density of the input sample data, a feature which is very valuable to applications where sample data are hard to obtain. This paper presents the framework and a sample implementation of the FEM-based approach along with some examples.
机译:可视化分散数据的一个关键挑战是正确地对样本数据建模,以便可以准确显示整个目标体积中的数据变化。常用的基于插值的方法不能令人满意,因为它在建模过程中经常生成物理上不可能的数据值。另外,它没有提供估计错误的系统方法。用于建模的插值方法通常与用于渲染的插值方法不同,这会导致不一致和错误表示。此外,由于插值方法固有的数据连续性假设,因此无法处理不连续性。为了消除这些问题和其他问题,我们构建了另一种分散数据可视化的方法。基于有限元方法(FEM),这种基于FEM的方法将数据的控制方程式纳入建模过程,以确保建模数据在物理上有意义。它提供了误差估计值,可以指导有限元网络的细化以获得所需的精度。它允许在建模过程中选择基础函数,以与渲染过程中使用的插值函数匹配,从而可以实现一致性。它借助双层方案来处理不连续性。此外,它将数据建模问题从插值问题转换为边值问题,从而降低了对输入样本数据密度的要求,这一功能对于难以获取样本数据的应用非常有价值。本文介绍了基于FEM的方法的框架和示例实现以及一些示例。

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