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步川, 张全杰, 汪云海, 蒋鹏. 可读性增强的流图生成[J]. 计算机辅助设计与图形学学报, 2021, 33(8): 1182-1190. DOI: 10.3724/SP.J.1089.2021.18688
引用本文: 步川, 张全杰, 汪云海, 蒋鹏. 可读性增强的流图生成[J]. 计算机辅助设计与图形学学报, 2021, 33(8): 1182-1190. DOI: 10.3724/SP.J.1089.2021.18688
Bu Chuan, Zhang Quanjie, Wang Yunhai, Jiang Peng. Streamgraph Generation with Enhanced Readability[J]. Journal of Computer-Aided Design & Computer Graphics, 2021, 33(8): 1182-1190. DOI: 10.3724/SP.J.1089.2021.18688
Citation: Bu Chuan, Zhang Quanjie, Wang Yunhai, Jiang Peng. Streamgraph Generation with Enhanced Readability[J]. Journal of Computer-Aided Design & Computer Graphics, 2021, 33(8): 1182-1190. DOI: 10.3724/SP.J.1089.2021.18688

可读性增强的流图生成

Streamgraph Generation with Enhanced Readability

  • 摘要: 为了增强流图可读性,帮助用户更高效地识别染色层,提出一种基于流图已有布局,优化流图中染色层的颜色分配与标签布局的方法.首先根据流图的布局数据建立其颜色分配评价函数,通过遗传算法进行颜色分配方案优化,最大化染色层之间的颜色差异和染色层与背景的亮度差异;然后在每个染色层上运行滑动窗口,通过最小二乘法拟合自动调整标签倾斜角度以适应染色层形状变化,得到标签尺寸自适应的标签布局结果.通过用户测试与定量评估,将文中方法与现有方法在多个真实和模拟数据集上进行实验的结果表明,该方法能够显著提高染色层的识别正确率,降低识别耗时,同时增大标签尺寸,从而有效地提高流图可读性.

     

    Abstract: In order to enhance the readability of the streamgraph and assist users identify the target layer more efficiently,a method to optimize the color assignment and label layout in streamgraph based on the existing layout of streamgraph is proposed.First,the color assignment evaluation function of the stream-graph is established according to the layout,and then the color assignment result is got which can maximize the color difference between layers as well as the luminance difference between the background color and layers through genetic algorithm.Secondly,the sliding window is used to traverse each layer,and the tilt angle of each label is automatically adjusted by least squares to fit the shape change of each layer.Then the label layout results are obtained with adaptive label size.The method is compared with existing methods on multiple real and simulated datasets through user study and quantitative evaluation.The results show that the method can significantly improve the recognition accuracy,reduce the recognition time of the layers,and in-crease the label size at the same time,which means it can improve the readability of the streamgraph effectively.

     

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