@article{Winnemoeller:2006:RTV,
optpostscript = {},
number = {3},
month = jul,
author = {Holger Winnem{\"o}ller and Sven C. Olsen and Bruce Gooch},
optkey = {},
optannote = {},
url = {http://www.videoabstraction.net/},
localfile = {papers/Winnemoeller.2006.RTV.pdf},
optkeywords = {},
doi = {http://doi.acm.org/10.1145/1141911.1142018},
optciteseer = {},
journal = SIGGRAPH2006,
volume = {25},
optwww = {},
title = {{R}eal-{T}ime {V}ideo {A}bstraction},
abstract = {We present an automatic, real-time video and image abstraction
framework that abstracts imagery by modifying the contrast of
visually important features, namely luminance and color opponency.
We reduce contrast in low-contrast regions using an approximation
to anisotropic diffusion, and artificially increase contrast in
higher contrast regions with difference-of-Gaussian edges. The
abstraction step is extensible and allows for artistic or
data-driven control. Abstracted images can optionally be stylized
using soft color quantization to create cartoon-like effects with
good temporal coherence. Our framework design is highly parallel,
allowing for a GPU-based, real-time implementation. We evaluate
the effectiveness of our abstraction framework with a user-study
and find that participants are faster at naming abstracted faces
of known persons compared to photographs. Participants are also
better at remembering abstracted images of arbitrary scenes in a
memory task.},
pages = {1221--1226},
year = {2006},
}
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