Learning Natural Colors for Image Recoloring
Date
2014Metadata
Show full item recordAbstract
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.
BibTeX
@article {10.1111:cgf.12498,
journal = {Computer Graphics Forum},
title = {{Learning Natural Colors for Image Recoloring}},
author = {Huang, Hao-Zhi and Zhang, Song-Hai and Martin, Ralph R. and Hu, Shi-Min},
year = {2014},
publisher = {The Eurographics Association and John Wiley and Sons Ltd.},
ISSN = {1467-8659},
DOI = {10.1111/cgf.12498}
}
journal = {Computer Graphics Forum},
title = {{Learning Natural Colors for Image Recoloring}},
author = {Huang, Hao-Zhi and Zhang, Song-Hai and Martin, Ralph R. and Hu, Shi-Min},
year = {2014},
publisher = {The Eurographics Association and John Wiley and Sons Ltd.},
ISSN = {1467-8659},
DOI = {10.1111/cgf.12498}
}