• DocumentCode
    3598548
  • Title

    Epipolar geometry estimation based on genetic algorithm under different strategies

  • Author

    Mingxing, Hu ; Qiang, Xing ; Baozong, Yuan ; Xiaofang, Tang

  • Author_Institution
    Inst. of Inf. Sci., Northern Jiaotong Univ., Beijing, China
  • Volume
    1
  • fYear
    2002
  • Firstpage
    885
  • Abstract
    The paper addresses the problem of robust fundamental matrix estimation employing a new method based on genetic algorithms under different strategies, which use each gene to stand for a pair of correspondences, take every chromosome as a minimum subset for epipolar geometry estimation, and compute the fundamental matrix according to the length of the chromosomes. The method eventually converges to a globally optimal solution and is relatively unaffected by outliers. Experiments with both synthetic data and real images show that our method is more robust and precise than other typical methods.
  • Keywords
    genetic algorithms; geometry; image processing; matrix algebra; parameter estimation; chromosomes; epipolar geometry estimation; fundamental matrix estimation; gene; genetic algorithm; globally optimal solution; perspective images; real images; stereo image processing; synthetic data; Biological cells; Computational geometry; Constraint theory; Equations; Genetic algorithms; Image converters; Information science; Layout; Noise robustness; Stability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing, 2002 6th International Conference on
  • Print_ISBN
    0-7803-7488-6
  • Type

    conf

  • DOI
    10.1109/ICOSP.2002.1181198
  • Filename
    1181198