Conference Proceeding
Segmentation and Visualization of Multivariate Features Using Feature-Local Distributions 公开 Deposited
https://scholar.colorado.edu/concern/conference_proceedings/fj236280j
- Abstract
- We introduce an iterative feature-based transfer function de- sign 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 exis- tence of two distinct structure populations in these data, which cannot be isolated or distinguished via traditional transfer functions based on global distributions.
- Creator
- Date Issued
- 2011-01-01
- Academic Affiliation
- Journal Title
- Journal Volume
- 6938.0
- File Extent
- 619-628
- Subject
- 最新修改
- 2020-01-09
- Resource Type
- 权利声明
- Language
关联
单件
缩略图 | 标题 | 上传日期 | 公开度 | 行动 |
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segmentationAndVisualizationOfMultivariateFeaturesUsingFea.pdf | 2019-12-18 | 公开 | 下载 |