Unsupervised colorization of black-and-white cartoons
Daniel Sykora, Jan Burianek, Jiri Zara
Proceedings of the 3rd international symposium on Non-photorealistic animation and rendering, 2004, pp. 121--127.
Abstract: We present a novel color-by-example technique which combines image segmentation, patch-based sampling and probabilistic reasoning. This method is able to automate colorization when new color information is applied on the already designed black-and-white cartoon. Our technique is especially suitable for cartoons digitized from classical celluloid films, which were originally produced by a paper or cel based method. In this case, the background is usually a static image and only the dynamic foreground needs to be colored frame-by-frame. We also assume that objects in the foreground layer consist of several well visible outlines which will emphasize the shape of homogeneous regions.
@inproceedings{10.1145-987657.987677,
author = {Daniel Sykora and Jan Burianek and Jiri Zara},
title = {Unsupervised colorization of black-and-white cartoons},
booktitle = {Proceedings of the 3rd international symposium on Non-photorealistic animation and rendering},
pages = {121--127},
year = {2004},
}
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