• DocumentCode
    2996149
  • Title

    A genetic off-line tuner for robotic humanoid visual perception

  • Author

    Jafari, Shahram ; Jarvis, Ray

  • Author_Institution
    Intelligent Robotics Res. Centre, Monash Univ., Clayton, Vic., Australia
  • Volume
    4
  • fYear
    2003
  • fDate
    8-12 Dec. 2003
  • Firstpage
    2769
  • Abstract
    Here, a robust tuner is presented that has been developed for support of early visual understanding by a robotic humanoid, sg1, under development. One of the achieved goals is to speed up the process of real-time segmentation by eliminating any tuning sessions from the online process and carrying them out offline. Effectiveness values (credits) assigned to stereo-based range findings and colour components (red, green, blue) are some of the tuned parameters. However, more than nine parameters (such as: stereo range finder search area, minimum and maximum size of regions, thresholds...) are tuned using a genetic algorithm. A novel idea for automatic evaluation of the region-edge segmentation has been applied as well.
  • Keywords
    genetic algorithms; image segmentation; neural nets; real-time systems; robot vision; visual perception; genetic algorithm; genetic offline tuner; neural network; real-time segmentation; robotic humanoid; stereo range finder search area; stereopsis; visual perception; Australia; Cameras; Genetic algorithms; Humanoid robots; Image segmentation; Intelligent robots; Neural networks; Robustness; Tuners; Visual perception;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2003. CEC '03. The 2003 Congress on
  • Print_ISBN
    0-7803-7804-0
  • Type

    conf

  • DOI
    10.1109/CEC.2003.1299439
  • Filename
    1299439