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Flow Visualization with Quantified Spatial and Temporal Errors Using Edge Maps

机译:使用边缘贴图以量化的时空误差进行流可视化

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Robust analysis of vector fields has been established as an important tool for deriving insights from the complex systems these fields model. Traditional analysis and visualization techniques rely primarily on computing streamlines through numerical integration. The inherent numerical errors of such approaches are usually ignored, leading to inconsistencies that cause unreliable visualizations and can ultimately prevent in-depth analysis. We propose a new representation for vector fields on surfaces that replaces numerical integration through triangles with maps from the triangle boundaries to themselves. This representation, called edge maps, permits a concise description of flow behaviors and is equivalent to computing all possible streamlines at a user defined error threshold. Independent of this error streamlines computed using edge maps are guaranteed to be consistent up to floating point precision, enabling the stable extraction of features such as the topological skeleton. Furthermore, our representation explicitly stores spatial and temporal errors which we use to produce more informative visualizations. This work describes the construction of edge maps, the error quantification, and a refinement procedure to adhere to a user defined error bound. Finally, we introduce new visualizations using the additional information provided by edge maps to indicate the uncertainty involved in computing streamlines and topological structures.
机译:矢量场的稳健分析已被确立为从这些场模型的复杂系统中获得见解的重要工具。传统的分析和可视化技术主要依靠通过数值积分的计算流线。通常会忽略这种方法固有的数值误差,从而导致不一致,从而导致可视化不可靠,并最终阻止深入分析。我们为表面上的矢量场提出了一种新的表示形式,该表示形式将通过三角形的数值积分替换为从三角形边界到其自身的贴图。这种表示形式称为边缘图,可以对流动行为进行简洁的描述,并且等效于在用户定义的错误阈值下计算所有可能的流线。独立于此误差,使用边缘图计算的流线可以保证在浮点精度之前保持一致,从而能够稳定提取诸如拓扑骨架之类的特征。此外,我们的表示法明确存储了空间和时间误差,这些误差可用于产生更多信息的可视化。这项工作描述了边缘贴图的构建,误差量化和完善过程,以遵守用户定义的误差范围。最后,我们使用边缘图提供的附加信息引入新的可视化,以指示计算流线和拓扑结构所涉及的不确定性。

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