Author： Lindner Albrecht Süsstrunk Sabine
Publisher： Society for Imaging Science and Technology
ISSN： 2166-9635
Source： Color and Imaging Conference, Vol.2013, Iss.1, 2013-01, pp. : 69-74
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Abstract
We present an automatic framework to extract color palettes from words. This is a novel approach in comparison to existing solutions, e.g. manual creation or extraction from images. The associations between words and colors are deduced from a large database of 6 million tagged images using a scalable data-mining technique. The palette creation can be constrained by the user to achieve a desired hue template. We first focus on single words and then extend to entire texts. We compare our results against Adobe Kuler, a widely used online platform of manually created color palettes. We show that our approach performs slightly better than its non-automatic counterpart in terms of user's preference rankings. This is a good result because our method is fully automatic whereas Kuler relies on users' palettes that are manually created and annotated.
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