Color Crafting: Automating the Construction of Designer Quality Color Ramps
Color Crafting: Automating the Construction of Designer Quality Color Ramps
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DOI：
10.1109/tvcg.2019.2934284
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发表时间：
2020-01-01
影响因子：
5.2
通讯作者：
Szafir, Danielle Albers
中科院分区：
文献类型：
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作者：
Smart, Stephen;Wu, Keke;Szafir, Danielle Albers
可视化通常使用顺序和发散色带对数值数据进行编码。有效的渐变使用足够可辨别的颜色，与数据很好地对齐，并且美观。设计师依靠多年的经验，创造出高品质的彩色坡道。然而，对于缺乏这种经验的新手可视化开发人员来说，制作有效的坡道是具有挑战性的，因为大多数构建坡道的指导方针都是松散定义的定性分析，通常难以应用。我们的目标是使可视化开发人员能够使用单个种子颜色轻松创建有效的颜色编码。我们使用一种算法方法来做到这一点，该方法通过分析设计师制作的颜色渐变结构中的模式来模拟设计师的实践。我们从222个专家设计的色带的语料库中构建这些模型，并使用结果自动生成模仿设计师实践的坡道。我们评估我们的方法，通过实证研究比较我们的方法与设计师制作的色带的输出。我们的模型产生的坡道，支持准确和美观的可视化至少以及设计师坡道，优于传统的数学方法。
Visualizations often encode numeric data using sequential and diverging color ramps. Effective ramps use colors that are sufficiently discriminable, align well with the data, and are aesthetically pleasing. Designers rely on years of experience to create high-quality color ramps. However, it is challenging for novice visualization developers that lack this experience to craft effective ramps as most guidelines for constructing ramps are loosely defined qualitative heuristics that are often difficult to apply. Our goal is to enable visualization developers to readily create effective color encodings using a single seed color. We do this using an algorithmic approach that models designer practices by analyzing patterns in the structure of designer-crafted color ramps. We construct these models from a corpus of 222 expert-designed color ramps, and use the results to automatically generate ramps that mimic designer practices. We evaluate our approach through an empirical study comparing the outputs of our approach with designer-crafted color ramps. Our models produce ramps that support accurate and aesthetically pleasing visualizations at least as well as designer ramps and that outperform conventional mathematical approaches.