Vector field reconstruction from sparse samples with applications

Marcos Lage, Fabiano Petronetto, Afonso Paiva, H. Lopes, T. Lewiner, G. Tavares
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引用次数: 17

Abstract

We present a novel algorithm for 2D vector field reconstruction from sparse set of points-vectors pairs. Our approach subdivides the domain adaptively in order to make local piecewise polynomial approximations for the field. It uses partition of unity to blend those local approximations together, generating a global approximation for the field. The flexibility of this scheme allows handling data from very different sources. In particular, this work presents important applications of the proposed method to velocity and acceleration fields' analysis, in particular for fluid dynamics visualization
稀疏样本的向量场重建及其应用
提出了一种基于点-向量对稀疏集的二维向量场重构算法。我们的方法自适应细分领域,以便对领域进行局部分段多项式逼近。它使用单位分割将这些局部近似混合在一起,生成场的全局近似。这种方案的灵活性允许处理来自不同来源的数据。特别地,这项工作展示了所提出的方法在速度和加速度场分析中的重要应用,特别是在流体动力学可视化方面
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