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Poisson-based tools for flow visualization

机译:基于泊松的流量可视化工具

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This paper applies Poisson-based methods to assist in interactive exploration of steady flow fields. Using data-driven deformations we obtain flow-orthogonal and flow-tangential surfaces by a flux-based optimization. Surfaces are positioned interactively and deformed in real-time according to local flow. The deformed surfaces are particularly useful for defining seed structures. We show how the same gradient-based computational framework can be applied to obtain parametrizations of flow-aligned surfaces. This way it is easy to define nontrivial seed structures for integration-based flow visualization methods. Additionally, the flow-aligned parametrizations are employed for view-independent surface-based LIC visualizations. We apply our method to a number of data sets to show the effectiveness of our deformations and parametrization-based seed extraction methods for interactive flow exploration.
机译:本文应用基于泊松的方法来协助稳定流场的交互式勘探。使用数据驱动的变形,我们通过基于通量的优化获得正交流和切线表面。可以交互式定位表面,并根据局部流动实时变形。变形的表面对于定义种子结构特别有用。我们展示了如何将相同的基于梯度的计算框架应用于获得流对齐曲面的参数化。通过这种方式,可以轻松地为基于集成的流可视化方法定义非平凡的种子结构。此外,将流对齐的参数化用于与视图无关的基于表面的LIC可视化。我们将我们的方法应用于许多数据集,以展示我们的变形和基于参数化的种子提取方法对于交互式流探索的有效性。

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