@techreport{Freeman:1999:AEB,
number = {TR-99-11},
optnote = {},
optaddress = {},
author = {William T. Freeman and Joshua B. Tenenbaum and Egon Pasztor},
optkey = {},
optannote = {},
opttype = {},
url = {http://www.merl.com/papers/docs/TR99-11.pdf},
localfile = {papers/Freeman.1999.AEB.pdf},
optmonth = {},
optdoi = {},
optstatus = {doi},
abstract = {training set of many different lines, each drawn by an artist in
various styles, which is used to translate new lines made by a
user into a particular desired style with a {it K-nearest
neighbor} algorithm. This algorithm fits each input line as a
linear combination of the several training lines in the same style
which are most similar to it. The fit line can then be rendered in
different styles because the training set contains versions of
each training line in each style. By describing input lines as
linear combinations of training set lines, this procedure is
expressive enough to fit a broad range of input drawings. By
restricting these linear combinations to contain only the most
similar training set lines, this procedure is constrained enough
to preserve the distinctive stylistic features of translated
lines. We represent input lines by splines with nonuniformly
spaced control points, which emphasizes these stylistic features.
Our example-based approach has a number of advantages over
conventional parameteric approaches to translating style. It can
handle styles which are difficult to describe parametrically, and
its repertoire can be easily extended by the user at any time.
Moreover, given appropriate representations, it can be generalized
to modify the style of other kinds of graphics objects, such as
the font of a letter or the movement style of an animated
character.},
title = {{A}n {E}xample-{B}ased {A}pproach to {S}tyle {T}ranslation for {L}ine
{D}rawings},
institution = {MERL -- A Mitsubishi Electric Research Laboratory},
year = {1999},
}
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