• DocumentCode
    575004
  • Title

    The background modeling for the video sequences using Radial Basis Function neural network

  • Author

    Rohanifar, Marjan ; Amiri, Ali

  • Author_Institution
    Comput. Eng., Islamic Azad Univ., Zanjan, Iran
  • fYear
    2011
  • fDate
    Nov. 29 2011-Dec. 1 2011
  • Firstpage
    371
  • Lastpage
    374
  • Abstract
    This paper an adapted background subtraction system based on Radial Basis Function neural network is given. In the suggested system for each background pixel a two-state machine is considered in which the RBF1 neural network is used for crossing between different states of the machine. In suggested system is flexible to light changes and very few movements of background object and the presence of new object in the background and other challenges mentioned in the field of estimate the background. The test are down on image group of Wallflower data set, the obtained result confirm the efficiency of the suggested solution.
  • Keywords
    image sequences; radial basis function networks; RBF neural network; Wallflower data set; background modeling; background subtraction system; radial basis function neural network; two-state machine; video sequences; Adaptation models; Biological neural networks; Estimation; Gaussian distribution; Radial basis function networks; Real-time systems; Surveillance; Background Estimation - RBF neural Networks - finite state machine;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Sciences and Convergence Information Technology (ICCIT), 2011 6th International Conference on
  • Conference_Location
    Seogwipo
  • Print_ISBN
    978-1-4577-0472-7
  • Type

    conf

  • Filename
    6316640