@inproceedings{Sykora:2004:UCB,
optorganization = {},
author = {Daniel S{\'{y}}kora and Jan Buri{\'{a}}nek and Ji{\v{r}}{\'{\i}}
{\v{Z}}{\'{a}}ra},
optkey = {},
optseries = {},
editor = {Aaron Hertzmann and Craig Kaplan},
localfile = {papers/Sykora.2004.UCB.pdf},
address = {New York},
publisher = {ACM Press},
optmonth = {},
doi = {http://doi.acm.org/10.1145/987657.987677},
opturl = {},
optwww = {},
optcrossref = {},
booktitle = NPAR2004,
optstatus = {},
optvolume = {},
optnumber = {},
title = {{U}nsupervised {C}olorization of {B}lack-and-{W}hite {C}artoons},
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 movie colorization when new color
information is applied on the already designed black-andwhite
cartoon. Our technique is especially suitable for cartoons
digitized from classical celluloid movies, which have been
originally produced by a paper or foil based method. In this case,
the background is a static image whilst 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.},
year = {2004},
pages = {121--128},
}
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