Interest point detection through multiobjective genetic programming

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@Article{Olague20122566,
  author =       "Gustavo Olague and Leonardo Trujillo",
  title =        "Interest point detection through multiobjective
                 genetic programming",
  journal =      "Applied Soft Computing",
  volume =       "12",
  number =       "8",
  pages =        "2566--2582",
  year =         "2012",
  ISSN =         "1568-4946",
  DOI =          "doi:10.1016/j.asoc.2012.03.058",
  URL =          "http://www.sciencedirect.com/science/article/pii/S1568494612001706",
  keywords =     "genetic algorithms, genetic programming,
                 Multiobjective optimisation, Interest point detection,
                 Evolutionary computer vision",
  abstract =     "The detection of stable and informative image points
                 is one of the most important low-level problems in
                 modern computer vision. This paper proposes a
                 multiobjective genetic programming (MO-GP) approach for
                 the automatic synthesis of operators that detect
                 interest points. The proposal is unique for interest
                 point detection because it poses a MO formulation of
                 the point detection problem. The search objectives for
                 the MO-GP search consider three properties that are
                 widely expressed as desirable for an interest point
                 detector, these are: (1) stability; (2) point
                 dispersion; and (3) high information content. The
                 results suggest that the point detection task is a MO
                 problem, and that different operators can provide
                 different trade-offs among the objectives. In fact,
                 MO-GP is able to find several sets of Pareto optimal
                 operators, whose performance is validated on
                 standardised procedures including an extensive test
                 with 500 images; as a result, we could say that all
                 solutions found by the system dominate previously
                 man-made detectors in the Pareto sense. In conclusion,
                 the MO formulation of the interest point detection
                 problem provides the appropriate framework for the
                 automatic design of image operators that achieve
                 interesting trade-offs between relevant performance
                 criteria that are meaningful for a variety of vision
                 tasks.",
}

Genetic Programming entries for Gustavo Olague Leonardo Trujillo

Citations