Evolutionary-computer-assisted design of image operators that detect interest points using genetic programming

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@Article{Olague2011,
  author =       "Gustavo Olague and Leonardo Trujillo",
  title =        "Evolutionary-computer-assisted design of image
                 operators that detect interest points using genetic
                 programming",
  journal =      "Image and Vision Computing",
  year =         "2011",
  volume =       "29",
  number =       "7",
  pages =        "484--498",
  ISSN =         "0262-8856",
  DOI =          "doi:10.1016/j.imavis.2011.03.004",
  URL =          "http://www.sciencedirect.com/science/article/B6V09-52GXV83-1/2/1462102339b445428fa4f2702939a41e",
  keywords =     "genetic algorithms, genetic programming, Interest
                 points, Computer assisted design, Evolutionary
                 computation, Evolutionary computer vision",
  size =         "15 pages",
  abstract =     "This work describes a way of designing interest point
                 detectors using an evolutionary computer-assisted
                 design approach. Nowadays, feature extraction is
                 performed through the paradigm of interest point
                 detection due to its simplicity and robustness for
                 practical applications such as: image matching and
                 view-based object recognition. Genetic programming is
                 used as the core functionality of the proposed
                 human-computer framework that significantly augments
                 the scope of interest point design through a computer
                 assisted learning process. Indeed, genetic programming
                 has produced numerous interest point operators, many
                 with unique or unorthodox designs. The analysis of
                 those best detectors gives us an advantage to achieve a
                 new level of creative design that improves the
                 perspective for human machine innovation. In
                 particular, we present two novel interest point
                 detectors produced through the analysis of multiple
                 solutions that were obtained through single and
                 multi-objective searches. Experimental results using a
                 well-known testbed are provided to illustrate the
                 performance of the operators and hence the
                 effectiveness of the proposal.",
}

Genetic Programming entries for Gustavo Olague Leonardo Trujillo

Citations