Automatic Construction of Image Transformations to Produce Variously Stylized Painterly Images

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Keita Nakayama and Tomoharu Nagao",
  title =        "Automatic Construction of Image Transformations to
                 Produce Variously Stylized Painterly Images",
  booktitle =    "European Modelling Symposium (EMS 2013)",
  year =         "2013",
  month =        "20-22 " # nov,
  pages =        "243--248",
  address =      "Manchester",
  keywords =     "genetic algorithms, genetic programming, ACTIT,
                 non-photorealistic rendering, painterly rendering",
  DOI =          "doi:10.1109/EMS.2013.42",
  abstract =     "We describe a new method that generates images that
                 represent various painting styles by constructing the
                 process of painterly rendering, using ACTIT (Automatic
                 Construction of Tree-structural Image Transformation).
                 ACTIT is an image processing system that automatically
                 constructs image transformations by using Genetic
                 Programming (GP) and image processing examples. The
                 constructed image transformations can then be applied
                 to other images. In our method, we add two extensions
                 to ACTIT so that it can be applied for constructing the
                 painterly rendering process. The first extension
                 comprises image processing filters that append
                 non-photo realistic effects. The second is our proposed
                 new fitness function of ACTIT for evaluating the
                 features of the images used for painterly rendering.
                 The results of experiments in which we used three
                 painting style examples show that our method constructs
                 three image transformations that produce the respective
                 painting styles.",
  notes =        "Also known as \cite{6779853}",

Genetic Programming entries for Keita Nakayama Tomoharu Nagao