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Learning Natural Colors for Image Recoloring
Author(s) -
Huang H.Z.,
Zhang S.H.,
Martin R. R.,
Hu S.M.
Publication year - 2014
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/cgf.12498
Subject(s) - artificial intelligence , computer science , probabilistic logic , property (philosophy) , computer vision , colored , graph , representation (politics) , image (mathematics) , pattern recognition (psychology) , theoretical computer science , philosophy , materials science , epistemology , politics , political science , law , composite material
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.