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Automatic Portrait Segmentation for Image Stylization
Author(s) -
Shen Xiaoyong,
Hertzmann Aaron,
Jia Jiaya,
Paris Sylvain,
Price Brian,
Shechtman Eli,
Sachs Ian
Publication year - 2016
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.12814
Subject(s) - portrait , computer science , segmentation , computer vision , artificial intelligence , computer graphics (images) , photography , image (mathematics) , exploit , painting , image segmentation , image processing , visual arts , art , computer security
Portraiture is a major art form in both photography and painting. In most instances, artists seek to make the subject stand out from its surrounding, for instance, by making it brighter or sharper. In the digital world, similar effects can be achieved by processing a portrait image with photographic or painterly filters that adapt to the semantics of the image. While many successful user‐guided methods exist to delineate the subject, fully automatic techniques are lacking and yield unsatisfactory results. Our paper first addresses this problem by introducing a new automatic segmentation algorithm dedicated to portraits. We then build upon this result and describe several portrait filters that exploit our automatic segmentation algorithm to generate high‐quality portraits.