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[Bax04]  Physically-Based Modeling Techniques for Interactive Digital Painting

Baxter:2004:PBM (PhD thesis)
Author(s)Baxter W.
Title« Physically-Based Modeling Techniques for Interactive Digital Painting »
SchoolDepartment of Computer Science, University of North Carolina
Year2004
AddressUSA
URLhttp://billbaxter.com/projects/index.html

Abstract
In this dissertation I present a novel, physically-based approach to digital painting. With the interactive simulation techniques I present, digital painters can work with digital brushes and paints whose behavior is similar to real ones. Using this physically-based approach, a digital painting system can provide artists with a versatile and expressive creative tool, while at the same time providing a more natural style of interaction enabled by the emulation of real-world implements. I introduce several specific modeling techniques for digital painting. First, I present a physically-based, 3D, deformable, virtual brush model based on non-linear quasi-static constrained energy minimization. The brush dynamics are computed using a skeletal physical model, which then determines the motion of a more complex geometric model. I also present three different models for capturing the dynamic behavior of viscous paint media, each offering a different trade-off between speed and fidelity—from 2D heuristics, to 3D partial differential equations. Accurate modeling of the optical behavior of paint mixtures and glazes is also important, and for this I present a real-time, physically-based rendering technique, based on the Kubelka-Munk equations and an eight-sample color space. Finally, I present techniques for modeling the haptic response of brushes in an artist’s hand, and demonstrate that all these techniques can be combined to provide the digital painter with an interactive, virtual painting system with a working style similar to real-world painting.

BibTeX code
@phdthesis{Baxter:2004:PBM,
  author = {William Baxter},
  optkey = {},
  optannote = {},
  opttype = {},
  url = {http://billbaxter.com/projects/index.html},
  title = {{P}hysically-{B}ased {M}odeling {T}echniques for {I}nteractive
           {D}igital {P}ainting},
  abstract = {In this dissertation I present a novel, physically-based approach
              to digital painting. With the interactive simulation techniques I
              present, digital painters can work with digital brushes and paints
              whose behavior is similar to real ones. Using this
              physically-based approach, a digital painting system can provide
              artists with a versatile and expressive creative tool, while at
              the same time providing a more natural style of interaction
              enabled by the emulation of real-world implements. I introduce
              several specific modeling techniques for digital painting. First,
              I present a physically-based, 3D, deformable, virtual brush model
              based on non-linear quasi-static constrained energy minimization.
              The brush dynamics are computed using a skeletal physical model,
              which then determines the motion of a more complex geometric
              model. I also present three different models for capturing the
              dynamic behavior of viscous paint media, each offering a different
              trade-off between speed and fidelity—from 2D heuristics, to 3D
              partial differential equations. Accurate modeling of the optical
              behavior of paint mixtures and glazes is also important, and for
              this I present a real-time, physically-based rendering technique,
              based on the Kubelka-Munk equations and an eight-sample color
              space. Finally, I present techniques for modeling the haptic
              response of brushes in an artist’s hand, and demonstrate that all
              these techniques can be combined to provide the digital painter
              with an interactive, virtual painting system with a working style
              similar to real-world painting.},
  localfile = {papers/Baxter.2004.PBM.pdf},
  address = {USA},
  school = {Department of Computer Science, University of North Carolina},
  optmonth = {},
  doi = {http://doi.acm.org/10.1145/1087318},
  year = {2004},
}

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