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[OSN+05]  Paintbrush Rendering of Lines using HMMs

Okabe:2005:PRL (In proceedings)
Author(s)Okabe Y., Saito S. and Nakajima M.
Title« Paintbrush Rendering of Lines using HMMs »
InProceedings of the 3[textsuperscript]rd International Conference on Computer Graphics and Interactive Techniques in Australasia and South East Asia (GRAPHITE'05, Dunedin, New Zealand)
Page(s)91--98
Year2005
PublisherACM Press
AddressNew York

Abstract
We propose a new method that emulates the expressive appearance of paintbrush strokes on paper. In our system, brush footprint characteristics are modeled using Hidden Markov Models (HMMs). Once the model is trained by a data set of given strokes, it estimates the most likely sequence of footprints for a given input line. The main difference between our method and other ones that use direct texture mapping lies in the estimation of the dynamic behavior of the footprints with respect to input lines. Since our method models simultaneously the physical characteristics of the brush and the drawing styles, it transforms input lines to aesthetic strokes which are really close to true ones, made with a real brush on a paper.

BibTeX code
@inproceedings{Okabe:2005:PRL,
  opteditor = {},
  optpostscript = {},
  optorganization = {},
  author = {Yuta Okabe and Suguru Saito and Masayuki Nakajima},
  optkey = {},
  optannote = {},
  optseries = {},
  address = {New York},
  localfile = {papers/Okabe.2005.PRL.pdf},
  optisbn = {},
  publisher = {ACM Press},
  optkeywords = {},
  doi = {http://doi.acm.org/10.1145/1101389.1101405},
  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 = {We propose a new method that emulates the expressive appearance of
              paintbrush strokes on paper. In our system, brush footprint
              characteristics are modeled using Hidden Markov Models (HMMs).
              Once the model is trained by a data set of given strokes, it
              estimates the most likely sequence of footprints for a given input
              line. The main difference between our method and other ones that
              use direct texture mapping lies in the estimation of the dynamic
              behavior of the footprints with respect to input lines. Since our
              method models simultaneously the physical characteristics of the
              brush and the drawing styles, it transforms input lines to
              aesthetic strokes which are really close to true ones, made with a
              real brush on a paper.},
  title = {{P}aintbrush {R}endering of {L}ines using {HMM}s},
  year = {2005},
  pages = {91--98},
}

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