• DocumentCode
    3212748
  • Title

    Video-based face recognition using manifold learning by neural networks

  • Author

    Hamedani, Kian ; Salehi, Seyyed Ali Seyyed

  • Author_Institution
    Biomed. Eng. Dept., Amirkabir Univ. of Technol., Tehran, Iran
  • fYear
    2012
  • fDate
    15-17 May 2012
  • Firstpage
    789
  • Lastpage
    793
  • Abstract
    This paper proposes a method using manifold learning by neural networks for identifying people while they are talking. In training phase people say the same sentence, we train the NN for learning low-dimensional nonlinear manifolds that are embedded in high-dimensional video space. After training phase we use another video of the same persons while they are saying another sentence for testing. Comparing the recognition results with other methods shows that our method outperforms other methods. Finally we achieve 98.4% of recognition rate.
  • Keywords
    face recognition; learning (artificial intelligence); neural nets; video signal processing; NN; high-dimensional video space; low-dimensional nonlinear manifold learning; neural networks; people identification; video-based face recognition; Artificial neural networks; Hidden Markov models; Manifolds; Principal component analysis; Testing; Videos; Neural Networks; face recognition; manifold; video;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical Engineering (ICEE), 2012 20th Iranian Conference on
  • Conference_Location
    Tehran
  • Print_ISBN
    978-1-4673-1149-6
  • Type

    conf

  • DOI
    10.1109/IranianCEE.2012.6292461
  • Filename
    6292461