基于线积分卷积的大规模图可视化  

Visualizing Large-Scale Graph Based on Line Integral Convolution

作　　者：雷辉[1,2] 张嘉伟[2] 陈海东[2] 解聪[2] 刘真[3] 李昕[2,4] 陈为[2] 

机构地区：[1]长沙理工大学电气与信息工程学院,长沙410004 [2]浙江大学CAD&CG国家重点实验室,杭州310058 [3]杭州电子科技大学计算机学院,杭州310018 [4]中国石油大学(华东)计算机与通信工程学院,青岛266555

出　　处：《计算机辅助设计与图形学学报》2013年第9期1288-1295,共8页Journal of Computer-Aided Design & Computer Graphics

基　　金：国家"八六三"高技术研究发展计划(2012AA120903);国家自然科学基金(61232012;61202279);教育部博士点基金(20120101110134)

摘　　要：传统的基于边-节点的大规模图可视化方法存在边交叉和节点覆盖等问题,其可视化结果不易于理解,为此提出一种基于线积分卷积的大规模图可视化方法.首先根据图的布局结果对每个节点的连接关系进行聚类,并提取其主要连接方向,以此重建出一个可近似描述原始图中节点之间连接关系的向量场;然后采用线积分卷积可视化该向量场,得到最终的可视化结果.实验结果表明,该方法不仅可避免大规模图中因边交叉和节点覆盖所带来的视觉混乱,还可以显式地揭示埋没于边中的节点连接细节信息.Conventional nodeqink based large graph visualization suffers heavy visual clutter due to edge crossing and node-edge overlapping, making the results difficult to explore. This paper proposes a novel method to visualize large-scale graph based on Line Integral Convolution. First, the connection relationship is clustered for each node with respect to the initial layout. The main connection orientations are then extracted to direct the generation of a synthetic vector field, which approximately describes the connection relationship in the input graph. Finally, LIC is employed to visualize this synthetic vector field. Experimental results demonstrate that our method is capable of releasing the visual clutter, and can reveal connection details hidden in edge crossing regions.

关 键 词：图可视化 线积分卷积 大规模图 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]