Towards Automated Artificial Evolution for Computer-generated Images   [AE]

by

Baluja, S., Pomerleau, D. and Jochem, T.

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Info: Connection Science (Journal), 1994, p. 325-354
Keywords:genetic algorithms, genetic programming, artificial neural networks (ANN), simulated evolution, computer graphics
Abstract:
In 1991, Karl Sims presented work on artificial evolution [AE] in which he used genetic algorithms to evolve complex structures [GA] for use in computer generated images and animations. The evolution of the computer generated images progressed from simple, randomly generated shapes to interesting images which the users interactively created. The evolution advanced under the constant guidance and supervision of the user. This paper describes attempts to automate the process of image evolution through the use of artificial neural networks. [ANN] [NN] The central objective of this study is to learn the user's preferences, and to apply this knowledge to evolve aesthetically pleasing images which are similar to those evolved through interactive sessions with the user. This paper presents a detailed analysis of both the shortcomings and successes encountered in the use of five artificial neural network architectures. [NN] Further possibilities for improving the performance of a fully automated system are also discussed.
Notes:
also CMU techical report CMU//CS-93-198
Author(s) DL:Online papers for Baluja, S.
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BibTex:
@Article{baluja:1994:taaecgi,
  author =       "Shumeet Baluja and Dean Pomerleau and Todd Jochem",
  title =        "Towards Automated Artificial Evolution for
                 Computer-generated Images",
  journal =      "Connection Science",
  year =         "1994",
  volume =       "6",
  number =       "2 and 3",
  pages =        "325--354",
  keywords =     "genetic algorithms, genetic programming, artificial
                 neural networks (ANN), simulated evolution, computer
                 graphics",
  abstract =     "

                 In 1991, Karl Sims presented work on artificial
                 evolution in which he used genetic algorithms to evolve
                 complex structures for use in computer generated images
                 and animations. The evolution of the computer generated
                 images progressed from simple, randomly generated
                 shapes to interesting images which the users
                 interactively created. The evolution advanced under the
                 constant guidance and supervision of the user. This
                 paper describes attempts to automate the process of
                 image evolution through the use of artificial neural
                 networks. The central objective of this study is to
                 learn the user's preferences, and to apply this
                 knowledge to evolve aesthetically pleasing images which
                 are similar to those evolved through interactive
                 sessions with the user. This paper presents a detailed
                 analysis of both the shortcomings and successes
                 encountered in the use of five artificial neural
                 network architectures. Further possibilities for
                 improving the performance of a fully automated system
                 are also discussed.",
  notes =        "also CMU techical report CMU//CS-93-198

                 ",
}