| dc.contributor.author | Huang, Hao-Zhi | en_US |
| dc.contributor.author | Zhang, Song-Hai | en_US |
| dc.contributor.author | Martin, Ralph R. | en_US |
| dc.contributor.author | Hu, Shi-Min | en_US |
| dc.contributor.editor | J. Keyser, Y. J. Kim, and P. Wonka | en_US |
| dc.date.accessioned | 2015-03-03T12:54:08Z | |
| dc.date.available | 2015-03-03T12:54:08Z | |
| dc.date.issued | 2014 | en_US |
| dc.identifier.issn | 1467-8659 | en_US |
| dc.identifier.uri | http://dx.doi.org/10.1111/cgf.12498 | en_US |
| dc.description.abstract | We present a data-driven method for automatically recoloring a photo to enhance its appearance or change a viewer's emotional response to it. A compact representation called a RegionNet summarizes color and geometric features of image regions, and geometric relationships between them. Correlations between color property distributions and geometric features of regions are learned from a database of well-colored photos. A probabilistic factor graph model is used to summarize distributions of color properties and generate an overall probability distribution for color suggestions. Given a new input image, we can generate multiple recolored results which unlike previous automatic results, are both natural and artistic, and compatible with their spatial arrangements. | en_US |
| dc.publisher | The Eurographics Association and John Wiley and Sons Ltd. | en_US |
| dc.title | Learning Natural Colors for Image Recoloring | en_US |
| dc.description.seriesinformation | Computer Graphics Forum | en_US |
