基于泊松的流可视化工具

J. M. Esturo, M. Schulze, Christian Rössl, H. Theisel
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引用次数: 9

摘要

本文应用基于泊松的方法辅助定常流场的交互勘探。利用数据驱动的变形,通过基于流量的优化得到流量正交曲面和流量切向曲面。曲面可根据局部流动进行交互定位和实时变形。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准表面的参数化。这样就可以很容易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,流对齐参数化被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,以显示我们的变形和基于参数化的种子提取方法在交互式流探索中的有效性。
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Poisson-based tools for flow visualization
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.
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