@inproceedings{Chang:2005:EBC2,
opteditor = {},
optpostscript = {},
optorganization = {},
author = {Youngha Chang and Suguru Saito and Masayuki Nakajima},
optkey = {},
optannote = {},
optseries = {},
address = {New York},
localfile = {papers/Chang.2005.EBC2.pdf},
optisbn = {},
publisher = {ACM Press},
optkeywords = {},
doi = {http://doi.acm.org/10.1145/1101389.1101459},
optmonth = {},
optciteseer = {},
opturl = {},
optcrossref = {},
optwww = {},
booktitle = {Proceedings of the 3\textsuperscript{rd} International Conference
on Computer Graphics and Interactive Techniques in Australasia
and South East Asia (GRAPHITE'05, Dunedin, New Zealand)},
optvolume = {},
optnumber = {},
abstract = {Color is very important in setting the mood of images and video
sequences. For this reason, color transformation is one of the
most important features in photo-editing or video post-production
tools because even slight modifications of colors in an image can
strongly increase its visual appeal. However, conventional color
editing tools require user's manual operation for detailed color
manipulation. Such manual operation becomes burden especially when
editing video frame sequences. To avoid this problem, we
previously suggested a method [Chang et al. 2004] that performs an
examplebased color stylization of images using perceptual color
categories. In this paper, we extend this method to make the
algorithm more robust and to stylize the colors of video frame
sequences. The main extension is the following 5 points:
applicable to images taken under a variety of light conditions;
speeding up the color naming step; improving the mapping between
source and reference colors when there is a disparity in size of
the chromatic categories; separate handling of achromatic
categories from chromatic categories; and extending the algorithm
along the temporal axis to allow video processing. We present a
variety of results, arguing that these images and videos convey a
different, but coherent mood.},
title = {{E}xample-{B}ased {C}olor {T}ransformation for {I}mage and {V}ideo},
year = {2005},
pages = {347--353},
}
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