• Journal of Korea Multimedia Society
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• v.10 no.10
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• pp.1240-1250
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• 2007

We introduce technique for color transformation of characters between scenes in 2D animation. As colors are perceived differently owing to light source, so character colors like clothes, skin and so on are colored differently owing to atmosphere of each scene. This paper is made an attempt to solve mathematically color assignment of characters which has been worked by hand so far. We can find a matrix for color transformation of characters by appling principle of color stimulus to our algorithm. In scenes of existing 2D animation, basic colors and colors under light source of characters are used for the matrix. And matrixes are obtained for each scenes of 2D animation. If we are known basic colors of some characters, you can derive character colors under other light source environments using the matrix. Therefore, this paper describes automatic color transformation of characters between animation scenes.

• Journal of Korea Multimedia Society
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• v.11 no.9
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• pp.1286-1295
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• 2008

Colors of 2D animation characters are generally assigned by art directors' subjective color sense. Even same characters should be colored differently according to the mood of animation scenes. In this study, we introduce the model for automatic color transformation of characters by using neural network. It can not only create automatically colors of characters which are good matched with 2D animation scenes but also reproduce art directors' subjective color sense. Specifically, this neural network model is initially made to learn the patterns of color change between basic colors of characters and colors of characters in various scene. Then if you know basic colors of some characters, you can derive colors of characters under other light source environments using the learned neural network. Subjective ratings(which is adopted to verify the proposed model) by color experts on the automatically transformed colors showed that the colors created by the model tended to be evaluated natural.