• DocumentCode
    2216325
  • Title

    Selective motion detection by Genetic Programming

  • Author

    Shi, Qiao ; Song, Andy

  • fYear
    2011
  • fDate
    5-8 June 2011
  • Firstpage
    496
  • Lastpage
    503
  • Abstract
    Motion detection is a vital part of vision systems, either biological or computerized. Conventional motion detection methods in machine vision can differentiate moving objects from background, but cannot directly handle different types of motions. In this paper, we present Genetic Programming (GP) as a method which not only removes relatively stationary background, but also can be selective on what kind of motions to capture. Programs can be evolved to select a certain type of moving objects and ignore other motions. That is to select fast moving target and ignore slowing moving ones. Furthermore programs can be evolved to handle these tasks even when the camera itself is in relatively arbitrary motion. This general GP method does not require additional process to differentiate various types of motions.
  • Keywords
    computer vision; genetic algorithms; motion estimation; genetic programming; machine vision; selective motion detection; vision system; Cameras; Detectors; Motion detection; Pixel; Training; Vehicles; Videos;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation (CEC), 2011 IEEE Congress on
  • Conference_Location
    New Orleans, LA
  • ISSN
    Pending
  • Print_ISBN
    978-1-4244-7834-7
  • Type

    conf

  • DOI
    10.1109/CEC.2011.5949659
  • Filename
    5949659