Name
Abstract | ||
|---|---|---|
A model to rate color combinations that considers human aesthetic preferences is proposed. The proposed method does not assume that a color palette has a specific number of colors, i.e., input is not restricted to a two-, three-, or five-color palettes. We extract features from a color palette whose size does not depend on the number of colors in the palette. The proposed rating prediction model is trained using a human color preference dataset. The model allows a user to extend a color palette, e.g., from three colors to five or seven colors, while retaining color harmony. In addition, we present a color search scheme for a given palette and a customized version of the proposed model for a specific color tone. We demonstrate that the proposed model can also be applied to various palette-based applications. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1111/cgf.13010 | Comput. Graph. Forum |
Field | DocType | Volume |
Computer vision,Color space,Color histogram,Computer science,Web colors,Color depth,Color balance,Artificial intelligence,Color cycling,Color quantization,ICC profile | Journal | 35 |
Issue | ISSN | Citations |
7 | 0167-7055 | 4 |
PageRank | References | Authors |
0.38 | 13 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Naoki Kita | 1 | 15 | 9.62 |
| Kazunori Miyata | 2 | 161 | 41.73 |