• DocumentCode
    1592334
  • Title

    A novel fast motion estimation method based on genetic algorithm

  • Author

    Li, Shen ; Xu, Wei-pu ; Wang, Hui ; Zheng, Nan-ning

  • Author_Institution
    Inst. of Artificial Intelligence & Robotics, Xi´´an Jiaotong Univ., China
  • Volume
    1
  • fYear
    1999
  • fDate
    6/21/1905 12:00:00 AM
  • Firstpage
    66
  • Abstract
    A novel fast motion estimation method based on an improved genetic algorithm is presented, in which both objective search and random search derived from genetic mutation are used for searching the global optimum and a threshold selection operator is applied to speeding up the estimation. The selection of initial population based on the coherence between neighboring macroblocks also improves the performance of search. Experimental results demonstrate that this method has very similar performance to that of FS, but just slightly slower than 3SS and 2DL. The inherent robustness and high parallelism enable it to be suitable for VLSI implementation of video encoders
  • Keywords
    genetic algorithms; motion estimation; performance evaluation; search problems; VLSI; experimental results; fast motion estimation method; genetic algorithm; genetic mutation; global optimum; objective search; parallelism; performance; random search; threshold selection operator; video encoders; Artificial intelligence; Computational complexity; Encoding; Genetic algorithms; Genetic mutations; Intelligent robots; Motion estimation; Parallel processing; Robustness; Very large scale integration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 1999. ICIP 99. Proceedings. 1999 International Conference on
  • Conference_Location
    Kobe
  • Print_ISBN
    0-7803-5467-2
  • Type

    conf

  • DOI
    10.1109/ICIP.1999.821566
  • Filename
    821566