论文标题
图标的字形 - 自动产生隐喻字形
Glyph from Icon -- Automated Generation of Metaphoric Glyphs
论文作者
论文摘要
隐喻的字形通过建立与基本问题域的图形实体建立图形实体来增强用于可视化定量多维数据的抽象字形的可读性和可学习性。但是，它们的构建主要是手动过程。在本文中，我们介绍了glyph-from-icon（GFI）方法，该方法允许从用户指定的图标中自动生成隐喻字形。我们的方法使用多达七个可量化的视觉变量修改了图标的视觉外观，其中三个操纵其几何形状，而四个会影响其颜色。根据可视化目标，这些视觉变量的特定组合定义了用于数据编码的字形变量。从技术上讲，我们提出了一个基于扩散的参数图标表示，该表示包括与几何和基于颜色的视觉变量相关的自由度。此外，我们扩展了GFI方法以实现生成的字形的可伸缩性。基于用户研究，我们评估了对字形的主要变量的感知，即几何和颜色调制的幅度和频率，作为刺激的函数，推断功能关系以及量化水平，以达到感知单调性和可读性。最后，我们提出了可视化变量的可牢固可感知的组合，我们将其应用于COVID-19数据的可视化。
Metaphoric glyphs enhance the readability and learnability of abstract glyphs used for the visualization of quantitative multidimensional data by building upon graphical entities that are intuitively related to the underlying problem domain. Their construction is, however, a predominantly manual process. In this paper, we introduce the Glyph-from-Icon (GfI) approach that allows the automated generation of metaphoric glyphs from user specified icons. Our approach modifies the icon's visual appearance using up to seven quantifiable visual variables, three of which manipulate its geometry while four affect its color. Depending on the visualization goal, specific combinations of these visual variables define the glyphs's variables used for data encoding. Technically, we propose a diffusion-curve based parametric icon representation, which comprises the degrees-of-freedom related to the geometric and color-based visual variables. Moreover, we extend our GfI approach to achieve scalability of the generated glyphs. Based on a user study we evaluate the perception of the glyph's main variables, i.e., amplitude and frequency of geometric and color modulation, as function of the stimuli and deduce functional relations as well as quantization levels to achieve perceptual monotonicity and readability. Finally, we propose a robustly perceivable combination of visual variables, which we apply to the visualization of COVID-19 data.
