基于聚类的二维向量场可视化  

Clustering Based 2D Vector Field Visualization

作　　者：王少荣[1,2] 汪国平[2,3] 

机构地区：[1]北京林业大学信息学院,北京100083 [2]北京市虚拟仿真与可视化工程技术研究中心,北京100871 [3]北京大学图形与交互技术实验室,北京100871

出　　处：《计算机辅助设计与图形学学报》2014年第10期1593-1602,共10页Journal of Computer-Aided Design & Computer Graphics

基　　金：北京林业大学新进教师科研启动基金(BLX2011019);国家"九七三"重点基础研究发展计划项目(2010CB328002);国家自然科学基金(61173080)

摘　　要：已有的二维流场可视化中,鞍点等临界点是最重要的特征之一.文中从一个新的角度提出一种基于流线聚类的二维向量场可视化方法.首先生成采样流线集合,然后将流线聚类,最后引入共轭法向量场和流线密度矩阵对同一个类的流线进行加速排序.在此基础上,提出3种可视化应用:抽取每一类的代表流线进行向量场的流线简洁表达;根据流线之间距离进行多分辨率均匀流线表达;生成权值图,增强基于纹理的向量场可视化.实验结果表明,该方法具有良好的鲁棒性,可视化效果优于已有的方法.Critical points such as saddle point are one set of the most important features in 2D vector field visualization methods. A novel clustering based approach is proposed in this paper. First, a set of streamlines are generated, and are clustered into different groups. Conjugated normal vector field and dense matrices are introduced to accelerate the sorting of the streamlines in each group. Thereafter, different post-processes can be performed according to various visualization applications, a streamline simplification that works for each group; a multi-resolution evenly-spaced streamline placement based on streamline proximity; an enhanced texture based visualization based on the weighted matrix. Experiments show that our results are satisfactory and robust.

关 键 词：向量场可视化 聚类 向量场简化 密度矩阵 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]