Evolvable 3D Modeling for Model-Based Object Recognition Systems

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InCollection{kinnear:nguyen,
  title =        "Evolvable {3D} Modeling for Model-Based Object
                 Recognition Systems",
  author =       "Thang Nguyen and Thomas Huang",
  booktitle =    "Advances in Genetic Programming",
  publisher =    "MIT Press",
  editor =       "Kenneth E. {Kinnear, Jr.}",
  year =         "1994",
  chapter =      "22",
  pages =        "459--475",
  size =         "17 pages",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://www.amazon.co.uk/Advances-Genetic-Programming-Complex-Adaptive/dp/0262111888",
  URL =          "http://cognet.mit.edu/sites/default/files/books/9780262277181/pdfs/9780262277181_chap22.pdf",
  abstract =     "This paper presents a system that evolves 3D models
                 over time, eventually producing novel models that are
                 more desirable than initial models. The algorithm
                 starts with some crude models given by the user, or
                 randomly-generated models from a given model-grammar
                 with generic design rules and loose constraints. The
                 underlying philosophy here is of gradually evolving the
                 initial models into better models over many
                 generations. There is a close analog in the evolution
                 of species where better-fit species gradually emerge
                 and form specialised niches, a highly efficient process
                 of complex structural and functional optimization. Our
                 simulation results for 3D jet aircraft model design
                 illustrate that this approach to model design and
                 refinement is feasible and effective. The intended
                 application domain is for automatic object recognition
                 system, though the model fitness criteria is currently
                 determined by user interactive selection.",
  notes =        "GP on very small populations (10). Very powefull,
                 aircraft design, primatives

                 see also
                 http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/ftp.io.com/papers/gp-3D-modeling.ps.Z

                 ",
}

Genetic Programming entries for Thang C Nguyen Thomas S Huang

Citations