An efficient control over human running animation with extension of planar hopper model

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@Article{Young-MinKang:1999:echraephm,
  author =       "Young-Min Kang and Hwan-Gue Cho and Ee-Taek Lee",
  title =        "An efficient control over human running animation with
                 extension of planar hopper model",
  journal =      "The Journal of Visualization and Computer Animation",
  year =         "1999",
  volume =       "10",
  number =       "4",
  pages =        "215--224",
  keywords =     "genetic algorithms, genetic programming, animation,
                 human gait, energy control",
  ISSN =         "1049-8907",
  URL =          "http://www3.interscience.wiley.com/cgi-bin/abstract/68501003/START",
  DOI =          "DOI:10.1002/(SICI)1099-1778(199910/12)10:4<215::AID-VIS209>3.0.CO;2-W",
  size =         "10 pages",
  abstract =     "The most important goal of character animation is to
                 efficiently control the motions of a character. Until
                 now, many techniques have been proposed for human gait
                 animation. Some techniques have been created to control
                 the emotions in gaits such as tired walking and brisk
                 walking by using parameter interpolation or motion data
                 mapping. Since it is very difficult to automate the
                 control over the emotion of a motion, the emotions of a
                 character model have been generated by creative
                 animators. This paper proposes a human running model
                 based on a one-legged planar hopper with a
                 self-balancing mechanism. The proposed technique
                 exploits genetic programming to optimize movement and
                 can be easily adapted to various character models. We
                 extend the energy minimization technique to generate
                 various motions in accordance with emotional
                 specifications. Copyright c 1999 John Wiley & Sons,
                 Ltd.",
}

Genetic Programming entries for Young-Min Kang Hwan-Gue Cho Ee-Taek Lee

Citations