Combustion Research Facility, Sandia National Laboratories, Livermore, CA 94551-0969, USA.
IEEE Trans Vis Comput Graph. 2012 Aug;18(8):1353-67. doi: 10.1109/TVCG.2011.155.
Effective 3D streamline placement and visualization play an essential role in many science and engineering disciplines. The main challenge for effective streamline visualization lies in seed placement, i.e., where to drop seeds and how many seeds should be placed. Seeding too many or too few streamlines may not reveal flow features and patterns either because it easily leads to visual clutter in rendering or it conveys little information about the flow field. Not only does the number of streamlines placed matter, their spatial relationships also play a key role in understanding the flow field. Therefore, effective flow visualization requires the streamlines to be placed in the right place and in the right amount. This paper introduces hierarchical streamline bundles, a novel approach to simplifying and visualizing 3D flow fields defined on regular grids. By placing seeds and generating streamlines according to flow saliency, we produce a set of streamlines that captures important flow features near critical points without enforcing the dense seeding condition. We group spatially neighboring and geometrically similar streamlines to construct a hierarchy from which we extract streamline bundles at different levels of detail. Streamline bundles highlight multiscale flow features and patterns through clustered yet not cluttered display. This selective visualization strategy effectively reduces visual clutter while accentuating visual foci, and therefore is able to convey the desired insight into the flow data.
有效的 3D 流线放置和可视化在许多科学和工程学科中起着至关重要的作用。有效流线可视化的主要挑战在于种子点的放置，即在哪里放置种子以及应该放置多少种子。放置过多或过少的流线可能无法揭示流场特征和模式，因为这容易导致渲染中的视觉混乱，或者对流场几乎没有信息。放置的流线数量不仅重要，它们的空间关系在理解流场方面也起着关键作用。因此，有效的流动可视化需要将流线放置在正确的位置和数量。本文介绍了层次流线束，这是一种简化和可视化规则网格上定义的 3D 流场的新方法。通过根据流显著性放置种子并生成流线，我们生成了一组流线，这些流线可以捕获关键点附近的重要流场特征，而无需强制密集的种子条件。我们将空间上相邻且几何相似的流线分组，以构建一个层次结构，从中提取不同细节层次的流线束。流线束通过聚类而不杂乱的显示方式突出显示多尺度的流场特征和模式。这种选择性可视化策略有效地减少了视觉混乱，同时突出了视觉焦点，因此能够传达对流动数据的预期洞察力。
