Exploring non-photorealistic rendering with genetic programming

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  author =       "Maryam Baniasadi and Brian J. Ross",
  title =        "Exploring non-photorealistic rendering with genetic
  journal =      "Genetic Programming and Evolvable Machines",
  year =         "2015",
  volume =       "16",
  number =       "2",
  pages =        "211--239",
  month =        jun,
  keywords =     "genetic algorithms, genetic programming, Evolutionary
  ISSN =         "1389-2576",
  DOI =          "doi:10.1007/s10710-014-9234-0",
  size =         "29 pages",
  abstract =     "The field of evolutionary art focuses on using
                 artificial evolution as a means for generating and
                 exploring artistic images and designs. Here, we use
                 evolutionary computation to generate painterly styles
                 of images. A source image is read into the system, and
                 a genetic program is evolved that will re-render the
                 image with non-photorealistic effects. A main
                 contribution of this research is that the colour mixing
                 expression is evolved, which permits a variety of
                 interesting NPR effects to arise. The mixing expression
                 evaluates mathematical properties of the dynamically
                 changing canvas, which results in the evolution of
                 adaptive NPR procedures. Automatic fitness evaluation
                 includes Ralph's aesthetic model, colour matching, and
                 direct luminosity matching. A few simple techniques for
                 economical brush stroke application on the canvas are
                 supported, which produce different stylistic effects.
                 Using our approach, a number of established, as well as
                 innovative, non-photorealistic painting effects were

Genetic Programming entries for Maryam Baniasadi Brian J Ross