ISSN 1000-1239 CN 11-1777/TP

计算机研究与发展 ›› 2017, Vol. 54 ›› Issue (4): 855-860.doi: 10.7544/issn1000-1239.2017.20151056

• 软件技术 • 上一篇    下一篇

基于图像的大规模数据集交互可视化

王弘堃,曹轶,肖丽   

  1. (北京应用物理与计算数学研究所 北京 100094) (whk@iapcm.ac.cn)
  • 出版日期: 2017-04-01
  • 基金资助: 
    国家自然科学基金项目(61232012);中国工程物理研究院科学技术发展基金重点基金项目(2014A0403019);计算物理重点实验室基金项目

Image-Based Interactive Visualization of Large-Scale Data Sets

Wang Hongkun, Cao Yi, Xiao Li   

  1. (Institute of Applied Physics and Computational Mathematics, Beijing 100094)
  • Online: 2017-04-01

摘要: 随着计算机性能的不断提高,大规模数值模拟的规模成倍增长.即使在大型可视化服务器上,针对这些模拟结果的大规模数据可视分析也难以进行流畅地交互.提出基于图像的交互分析方法并开发相应系统,可以预先生成多视角的可视化结果图像,基于这些图像可以在普通设备上实现3D可视化结果的交互分析与展示,可以交互改变观察视角,动态展示数值模拟全过程的可视化结果,可以有效提高数值模拟的效率.

关键词: 可视化, 大规模数值模拟, 交互式绘制, 基于图像, 时变数据集

Abstract: With the development of supercomputers, the parallel scale of numerical simulations is increasing exponentially. It is a time-consuming task to visualize the data sets of ever-increasing scale output in the simulations. It is difficult or even impossible to analyze the data sets smoothly, even on a visualization server of high performance. To achieve good interactivity and display effect, an efficient image-based approach is proposed in this paper, and a corresponding software system is also developed. Firstly, typical visual analysis patterns are summarized based on domain knowledge. These patterns can commendably depict inner physical characters in a simulated data field. Secondly, based on these patterns, a set of high-resolution images are pre-generated from large-scale time-varying data sets on a supercomputer. These images are rendered at various viewpoints around the data field and then organized according to the patterns and the time steps. Thirdly, we analyze the simulated data field interactively from these visualization images on a common computer. These visualization images can be observed from different directions by changing the viewpoint interactively. They can also be shown in proper resolution according to the size of the observing window. As a result, the entire time-varying evolution of physical characters can be interactively explored at different viewpoints in proper resolution. The proposed approach does not suffer from large scale of data sets and high computational complexity of visualization and thus significantly improves the visual analysis efficiency for large-scale data sets from the simulations.

Key words: visualization, large-scale simulation, interactive rendering, image-based, time-varying data sets

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