Integrated Analysis and Display of Multivariate and Time- Dependent Data

9215145 Hesselink实验和数值技术都变得越来越复杂，导致了描述复杂物理现象的非常大的多元、时间相关的数据集。用于分析和显示这些数据集的可视化方法目前还不充分，特别是在处理张量数据时。该项目通过研究一种基于特征提取、数据压缩和沉浸式环境的集成方法，解决了更好地理解这些数据集的需求。增加复杂性的三维数据集：张量数据和时间相关字段将被显示和分析。大部分的研究工作都是为了理解产生这些大型多元数据集的物理系统的动态特性。因此，必须扩展用于显示稳定场的技术，以便显示与时间相关的数据。与时间相关的数据可以通过单个时间步骤的动画处理。然而，动画的处理时间是出了名的长。因此，在综合可视化过程的几个阶段正在研究数据压缩。在分析组件中，张量场的数据压缩是基于利用张量场拓扑提取和显示超粒子路径。在显示组件中，可以使用先进的数据压缩技术（如矢量聚类和4-D变换）分析和显示与时间相关的字段。最后，这些分析的结果显示了来自沉浸式环境的工具，应用于渲染方法的数据压缩技术，以及其他新技术。* * * v s t @ j l WINMINE HLP @ j j 1 WINTUTORDAT @ j j写HLP @ j k CALC EXE @ j @ CALC HLP @ j F CALENDARHLP @ j P峡谷中 @ j CHITZ BMP @ jı米丁WAV @ j N - 9215145 Hesselink实验和数值技术越来越复杂,主要对非常大的multiv K 7 $ $ $(F / K / 1 Courier符号& & Arial 5 Courier New Z " h lc lc r （S r:\WW20USER\ABSTRACT.）DOT摘要Alicia E. Harris

9215145 Hesselink Both experimental and numerical techniques are becoming more sophisticated leading towards very large multivariate, time-dependent datasets describing complex physical phenomena. Visualization approaches for analysis and display of these datasets are currently inadequate, in particular when dealing with tensor data. The project addresses the need for better understanding of these datasets by investigating an integrated approach based on the triad of enabling technologies of feature extraction, data compression, and immersive environments. Three-dimensional datasets of increased complexity: tensor data and time-dependent fields will be displayed and analyzed. Most of the research effort is aimed at understanding the dynamical properties of physical systems that give rise to these large multivariate datasets. Therefore, techniques used for visualizing steady fields must be extended in order to visualize time-dependent data. Time-dependent data may be handled by animation of the individual time steps. Processing time for animations, however, are notoriously long. Therefore, data compression is being investigated at several stages of the integrated visualization process. In the analysis component, data compression of tensor fields is based on extracting and displaying hyperparticle paths using tensor field topology. In the display component, time-dependent fields may be analyzed and displayed using advanced data compression techniques such as vector clustering and 4-D transforms. Finally, the results of these analysis are displayed with tools from immersive environments, data compression techniques applied to rendering approaches, and other new technologies. *** v s t @ j l WINMINE HLP @ j J 1 WINTUTORDAT @ j j WRITE HLP @ j k CALC EXE @ j @ CALC HLP @ j F CALENDARHLP @ j P CANYON MID @ j CHITZ BMP @ j ı M DING WAV @ j N- 9215145 Hesselink Both experimental and numerical techniques are becoming more sophisticated leading towards very large multiv K 7 $ $ $ ( F / K / 1 Courier Symbol & Arial 5 Courier New Z " h lc lc r ( S R:\WW20USER\ABSTRACT.DOT abstract Alicia E. Harris Alicia E. Harris