Understanding of GP-Evolved Motion Detectors

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Andy Song and Qiao Shi and Wei Yin",
  journal =      "IEEE Computational Intelligence Magazine",
  title =        "Understanding of GP-Evolved Motion Detectors",
  year =         "2013",
  volume =       "8",
  number =       "1",
  month =        feb,
  pages =        "46--55",
  size =         "7 pages",
  abstract =     "Evolving solutions for machine vision applications has
                 gained more popularity in the recent years. One area is
                 evolving programs by Genetic Programming (GP) for
                 motion detection, which is a fundamental component of
                 most vision systems. Despite the good performance, this
                 approach is not widely accepted by mainstream vision
                 application developers. One of the reasons is that
                 these GP generated programs are often difficult to
                 interpret by humans. This study analyses the reasons
                 behind the good performance and shows that the
                 behaviours of these evolved motion detectors can be
                 explained. Their capabilities of ignoring uninteresting
                 motions, differentiating fast motions from slow
                 motions, identifying genuine motions from moving
                 background and handling noises are not random. On
                 simplified problems we can reveal the behaviours of
                 these programs. By understanding the evolved detectors,
                 we can consider evolution as a good approach for
                 creating motion detection modules.",
  keywords =     "genetic algorithms, genetic programming, computer
                 vision, image motion analysis, object detection,
                 GP-evolved motion detector, evolution approach, machine
                 vision application, motion detection, motion
                 differentiation, vision system, Detectors, Human
                 factors, Machine vision, Motion detection, Noise
                 measurement, Videos",
  DOI =          "doi:10.1109/MCI.2012.2228594",
  ISSN =         "1556-603X",
  notes =        "Also known as \cite{6410722}",

Genetic Programming entries for Andy Song Qiao Shi Wei Yin