Journal
COMPUTER GRAPHICS FORUM
Volume 32, Issue 3, Pages 401-410Publisher
WILEY
DOI: 10.1111/cgf.12127
Keywords
H; 5; m [Information Interfaces]: MiscColor
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Funding
- NSF [IIS-1017745]
- Direct For Computer & Info Scie & Enginr [1016920] Funding Source: National Science Foundation
- Direct For Computer & Info Scie & Enginr
- Div Of Information & Intelligent Systems [1017745] Funding Source: National Science Foundation
- Div Of Information & Intelligent Systems [1016920] Funding Source: National Science Foundation
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We introduce an algorithm for automatic selection of semantically-resonant colors to represent data (e.g., using blue for data about oceans, or pink for love). Given a set of categorical values and a target color palette, our algorithm matches each data value with a unique color. Values are mapped to colors by collecting representative images, analyzing image color distributions to determine value-color affinity scores, and choosing an optimal assignment. Our affinity score balances the probability of a color with how well it discriminates among data values. A controlled study shows that expert-chosen semantically-resonant colors improve speed on chart reading tasks compared to a standard palette, and that our algorithm selects colors that lead to similar gains. A second study verifies that our algorithm effectively selects colors across a variety of data categories.
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