Evolving Frame Splitters by Genetic Programming

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

@InProceedings{Feng:2012:CEC,
  title =        "Evolving Frame Splitters by Genetic Programming",
  author =       "Xie Feng and Andy Song",
  pages =        "1466--1472",
  booktitle =    "Proceedings of the 2012 IEEE Congress on Evolutionary
                 Computation",
  year =         "2012",
  editor =       "Xiaodong Li",
  month =        "10-15 " # jun,
  DOI =          "doi:10.1109/CEC.2012.6256161",
  address =      "Brisbane, Australia",
  ISBN =         "0-7803-8515-2",
  keywords =     "genetic algorithms, genetic programming, Evolutionary
                 Computer Vision",
  abstract =     "This paper extends the application of Genetic
                 Programming into a new area, automatically splitting
                 video frames based on the content. A GP methodology is
                 presented to show how to evolve a program which can
                 analyse the difference between scenes and split them
                 accordingly. A few different approaches have been
                 investigated in this study. Compared with human written
                 video splitting programs, GP generated splitters are
                 more accurate. Moreover, it is shown that these video
                 splitting programs have high tolerance to noises. They
                 can still achieve reasonable performance even when the
                 videos are not easily recognisable by eyes due to the
                 server artificial noises.",
  notes =        "WCCI 2012. CEC 2012 - A joint meeting of the IEEE, the
                 EPS and the IET.",
}

Genetic Programming entries for Feng Xie Andy Song

Citations