Engineering of Computer Vision Algorithms Using Evolutionary Algorithms

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{DBLP:conf/acivs/Ebner09,
  author =       "Marc Ebner",
  title =        "Engineering of Computer Vision Algorithms Using
                 Evolutionary Algorithms",
  booktitle =    "Proceedings of the 11th International Conference on
                 Advanced Concepts for Intelligent Vision Systems, ACIVS
                 2009",
  year =         "2009",
  editor =       "Jacques Blanc-Talon and Wilfried Philips and 
                 Dan Popescu and Paul Scheunders",
  series =       "Lecture Notes in Computer Science",
  volume =       "5807",
  pages =        "367--378",
  address =      "Bordeaux, France",
  month =        sep # " 28-" # oct # " 2",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming, Cartesian
                 genetic programming, GPU, OpenGLSL",
  isbn13 =       "978-3-642-04696-4",
  URL =          "http://www.ra.cs.uni-tuebingen.de/mitarb/ebner/research/publications/uniTu2/EvoCVengineering.pdf",
  DOI =          "doi:10.1007/978-3-642-04697-1_34",
  size =         "12 pages",
  abstract =     "Computer vision algorithms are currently developed by
                 looking up the available operators from the literature
                 and then arranging those operators such that the
                 desired task is performed. This is often a tedious
                 process which also involves testing the algorithm with
                 different lighting conditions or at different sites. We
                 have developed a system for the automatic generation of
                 computer vision algorithms at interactive frame rates
                 using GPU accelerated image processing. The user simply
                 tells the system which object should be detected in an
                 image sequence. Simulated evolution, in particular
                 Genetic Programming, is used to automatically generate
                 and test alternative computer vision algorithms. Only
                 the best algorithms survive and eventually provide a
                 solution to the user's image processing task.",
  notes =        "Interactive evolution of image processing software.
                 Realtime 30 seconds. OpenGL shader language. mip
                 mapping. nVidia GeForce 9600 GT/PCI/SEE2

                 ",
}

Genetic Programming entries for Marc Ebner

Citations