Evolving performance control systems for digital puppetry

Created by W.Langdon from gp-bibliography.bib Revision:1.4216

  author =       "Andrew Gildfind and Michael A. Gigante and 
                 Ghassan Al-Qaimari",
  title =        "Evolving performance control systems for digital
  journal =      "Journal of Visualization and Computer Animation",
  year =         "2000",
  volume =       "11",
  number =       "4",
  pages =        "169--183",
  month =        "3 " # oct,
  publisher =    "John Wiley & Sons, Ltd.",
  keywords =     "genetic algorithms, genetic programming, performance
                 animation, motion capture, performance control systems,
                 puppetry, adaptive user interfaces",
  URL =          "http://www3.interscience.wiley.com/cgi-bin/abstract/73502730/ABSTRACT",
  URL =          "http://visinfo.zib.de/EVlib/Show?EVL-2000-444",
  DOI =          "doi:10.1002/1099-1778(200009)11:4<169::AID-VIS217>3.0.CO;2-L",
  URL =          "http://citeseer.ist.psu.edu/cache/papers/cs/21796/http:zSzzSzgoanna.cs.rmit.edu.auzSz~gildfindzSzthesiszSzpdfzSzjvca.pdf/gildfind00evolving.pdf",
  URL =          "http://citeseer.ist.psu.edu/438189.html",
  size =         "16 pages",
  abstract =     "We describe a new approach for creating performance
                 control systems for digital puppetry. Genetic
                 programming with fitness values specified directly by
                 the puppeteer is used. A generic device and model
                 representation combined with the inherent domain
                 independence of the genetic programming paradigm allows
                 this approach to create control systems for arbitrary
                 combinations of input devices and models. In addition,
                 a number of unique interaction techniques have been
                 developed to support the user-directed search. In this
                 paper we introduce the approach, describe the
                 implementation and user interface and present the
                 results from a comprehensive evaluation with expert
                 users. We show that a search-based approach can provide
                 an effective alternative to manually designing
                 performance control systems and an elegant mechanism
                 for unifying low-level input devices with a broad range
                 of model control modes.",

Genetic Programming entries for Andrew Gildfind Michael A Gigante Ghassan Al-Qaimari