Segmentation and Visualization of Multivariate Features Using Feature-Local Distributions
Segmentation and Visualization of Multivariate Features Using Feature-Local Distributions
复制标题
使用特征局部分布的多元特征的分割和可视化
DOI：
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发表时间：
2011
期刊：
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通讯作者：
P. Mininni
中科院分区：
文献类型：
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作者：
Kenny Gruchalla;M. Rast;E. Bradley;P. Mininni
我们介绍了一种迭代的基于特征的传递函数设计，它提取并系统地将多变量特征局部统计信息合并到基于纹理的体绘制过程中。我们认为，交互式多变量特征-局部方法在研究模糊定义的特征时是有利的，因为它提供了一个物理上有意义的、数量丰富的环境，在这个环境中可以检查结构属性对识别参数的敏感性。我们通过将其应用于Taylor-Green湍流中的涡旋结构来证明该方法的有效性。我们的方法确定了在这些数据中存在两个不同的结构总体，这不能通过基于全球分布的传统传递函数来分离或区分。
We introduce an iterative feature-based transfer function design that extracts and systematically incorporates multivariate feature-local statistics into a texture-based volume rendering process. We argue that an interactive multivariate feature-local approach is advantageous when investigating ill-defined features, because it provides a physically meaningful, quantitatively rich environment within which to examine the sensitivity of the structure properties to the identification parameters. We demonstrate the efficacy of this approach by applying it to vortical structures in Taylor-Green turbulence. Our approach identified the existence of two distinct structure populations in these data, which cannot be isolated or distinguished via traditional transfer functions based on global distributions.