Bajaj Chandrajit, Gillette Andrew, Goswami Samrat
Center for Computational Visualization, University of Texas at Austin Austin, Texas 78712.
Math Vis. 2009 Jan 1;2009:45-58. doi: 10.1007/978-3-540-88606-8_4.
The selection of appropriate level sets for the quantitative visualization of three dimensional imaging or simulation data is a problem that is both fundamental and essential. The selected level set needs to satisfy several topological and geometric constraints to be useful for subsequent quantitative processing and visualization. For an initial selection of an isosurface, guided by contour tree data structures, we detect the topological features by computing stable and unstable manifolds of the critical points of the distance function induced by the isosurface. We further enhance the description of these features by associating geometric attributes with them. We then rank the attributed features and provide a handle to them for curation of the topological anomalies.
为三维成像或模拟数据的定量可视化选择合适的水平集是一个既基础又关键的问题。所选的水平集需要满足若干拓扑和几何约束,才能用于后续的定量处理和可视化。对于由轮廓树数据结构引导的等值面初始选择,我们通过计算由等值面诱导的距离函数的临界点的稳定和不稳定流形来检测拓扑特征。我们通过将几何属性与这些特征相关联来进一步增强对这些特征的描述。然后,我们对带属性的特征进行排序,并为它们提供一个处理方式,以管理拓扑异常。