感知增强类流场可视化方法研究与发展

第30卷第1期计算机辅助设计与图形学学报Vol.30No.1 2018年1月Journal of Computer-Aided Design & Computer Graphics Jan. 2018感知增强类流场可视化方法研究与发展

王松1,2), 吴斌1,3), 吴亚东2)*

1) (中国工程物理研究院电子工程研究所绵阳 621010)

2) (西南科技大学计算机科学与技术学院绵阳 621010)

3) (西南科技大学信息工程学院绵阳 621010)

(wyd028@https://www.360docs.net/doc/a46366351.html,)

摘要: 流场可视化作为科学可视化领域发展最早、应用最广泛的研究方向, 在帮助用户分析和理解复杂流场流动机理, 洞察流场物理现象并发现流动科学规律方面发挥着重要的支撑作用. 其中感知增强类流场可视化方法能够有效展现流场结构特征、各属性间的相互作用及其复杂的流动物理现象, 为用户提供良好的流场可视化分析环境, 提高流场科学数据处理效率和可视分析能力. 文中主要介绍了感知增强类流场可视化方法在工业设计、航空航天、生物医学以及其他交叉领域的应用. 抽象领域专家分析理解流场物理现象, 洞察流场数据集中蕴含的复杂物理规律的过程, 提出一个自顶向下的VCIH分析流程模型, 包括视觉接收、认知构建、交互参与和硬件辅助. 以VCIH模型为指导, 从视觉感知增强、流场物理过程增强、探索式交互增强和硬件依赖性增强4个方面综述了感知增强类流场可视化方法的研究现状, 并结合应用需求展望未来的发展趋势.

关键词: 视觉感知增强; 流场物理过程增强; 探索式交互增强; 硬件依赖性增强; VCIH模型

中图法分类号: TP391.41 DOI: 10.3724/SP.J.1089.2018.16925

Survey on Perception Enhanced Flow Visualization

Wang Song1,2), Wu Bin1,3), and Wu Yadong2)*

1) (Institute of Electronic Engineering, China Academy of Engineering Physics, Mianyang 621010)

2) (School of Computer and Technology, Southwest University of Science and Technology, Mianyang 621010)

3) (School of Information Engineering, Southwest University of Science and Technology, Mianyang 621010)

Abstract: As the main research direction which earliest developed and most widely used in the field of sci-entific visualization, flow visualization plays an underlying role in helping users analyze and comprehend complex flow mechanism, provide insight into flow physical phenomena and discover flow scientific laws.

And perception enhanced flow visualization as one of flow visualization methods, can show effectively the flow field structure characteristics, the interactions among various properties and complex flow physical phenomena, and it provides a favorable flow field visualization analysis environment to improve processing efficiency of flow scientific data and visual analysis ability. In this paper, we mostly introduce the applica-tions of perception enhanced flow visualization methods in a variety of areas, such as industrial design, aer-ospace, biomedicine and some cross-domain applications. A top-down VCIH model for flow visualization and analysis drawing from the experience of domain experts by analyzing flow physical phenomena and having an insight into the complicated physical regularities of flow field. This model includes vision, cogni-tion, interaction and hardware. According to the VCIH model, then we summarize visualization methods

收稿日期: 2017-10-13; 修回日期: 2017-11-14. 基金项目: 国家重点研究计划项目(2016QY04W0801); 四川省科技厅项目(2017TJPT0200, 2017KZ0023, 2017GZ0186). 王松(1989—), 男, 博士研究生, CCF会员, 主要研究方向为科学可视化、可视分析等; 吴斌(1965—), 男, 博士, 教授, 博士生导师, 主要研究方向为图像处理与模式识别、人工智能及其应用等; 吴亚东(1979—), 男, 博士, 教授, 博士生导师, CCF会员, 论文通讯作者, 主要研究方向为图像图形处理、可视化与可视分析等.

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