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Title: Semantic colorization with internet images
Authors: Chia, A.Y.-S.
Zhuo, S. 
Gupta, R.K.
Tai, Y.-W.
Cho, S.-Y.
Tan, P. 
Lin, S.
Issue Date: Dec-2011
Citation: Chia, A.Y.-S., Zhuo, S., Gupta, R.K., Tai, Y.-W., Cho, S.-Y., Tan, P., Lin, S. (2011-12). Semantic colorization with internet images. ACM Transactions on Graphics 30 (6) : -. ScholarBank@NUS Repository.
Abstract: Colorization of a grayscale photograph often requires considerable effort from the user, either by placing numerous color scribbles over the image to initialize a color propagation algorithm, or by looking for a suitable reference image from which color information can be transferred. Even with this user supplied data, colorized images may appear unnatural as a result of limited user skill or inaccurate transfer of colors. To address these problems, we propose a colorization system that leverages the rich image content on the internet. As input, the user needs only to provide a semantic text label and segmentation cues for major foreground objects in the scene. With this information, images are downloaded from photo sharing websites and filtered to obtain suitable reference images that are reliable for color transfer to the given grayscale photo. Different image colorizations are generated from the various reference images, and a graphical user interface is provided to easily select the desired result. Our experiments and user study demonstrate the greater effectiveness of this system in comparison to previous techniques. © 2011 ACM.
Source Title: ACM Transactions on Graphics
ISSN: 07300301
DOI: 10.1145/2024156.2024190
Appears in Collections:Staff Publications

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