• DocumentCode
    3100904
  • Title

    Human posture estimation from multiple images using genetic algorithm

  • Author

    Ohya, Jun ; Kishino, Fumio

  • Author_Institution
    ATR Commun. Syst. Res. Labs., Kyoto, Japan
  • Volume
    1
  • fYear
    1994
  • fDate
    9-13 Oct 1994
  • Firstpage
    750
  • Abstract
    A new method for estimating human postures at a time instant from multiple images using a genetic algorithm is proposed. The posture parameters to be estimated are assigned to the genes of individuals in the population. For each individual, its fitness evaluates to what extent the multiple human images synthesized by deforming a 3D human model according to the values of the genes are registered to the real multiple human images. Genetic operations such as natural selection, crossover and mutation are performed, and individuals in the next generation are generated. After a certain number of repetitions for these processes, the estimated parameter values are obtained from the individual with the best fitness. Experiments using synthesized human multiple images show promising results
  • Keywords
    image recognition; 3D human model; best fitness; crossover; genetic algorithm; human posture estimation; multiple images; mutation; natural selection; Deformable models; Genetic algorithms; Genetic mutations; Humans; Joints; Laboratories; Layout; Motion analysis; Parameter estimation; Visual communication;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 1994. Vol. 1 - Conference A: Computer Vision & Image Processing., Proceedings of the 12th IAPR International Conference on
  • Conference_Location
    Jerusalem
  • Print_ISBN
    0-8186-6265-4
  • Type

    conf

  • DOI
    10.1109/ICPR.1994.576430
  • Filename
    576430