• DocumentCode
    2497318
  • Title

    Orthogonal linear local spline discriminant embedding for face recognition

  • Author

    Lei, Ying-Ke ; Hu, Rong-Xiang ; Tang, Lei ; Zhang, Shan-Wen ; Huang, De-Shuang

  • Author_Institution
    Intell. Comput. Lab., Chinese Acad. of Sci., Hefei, China
  • fYear
    2010
  • fDate
    18-23 July 2010
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    In this paper, an efficient feature extraction algorithm called orthogonal linear local spline discriminant embedding (O-LLSDE) is proposed for face recognition. Derived from local spline embedding (LSE), O-LLSDE not only inherits the advantages of LSE which uses local tangent space as a representation of the local geometry so as to preserve the local structure, but also makes full use of class information and orthogonal subspace to improve discriminant power. Extensive experiments on standard face databases demonstrate the effectiveness of the proposed method.
  • Keywords
    face recognition; feature extraction; face recognition; feature extraction; local geometry representation; local spline embedding; local tangent space; orthogonal linear local spline discriminant embedding; standard face databases; Equations; Principal component analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), The 2010 International Joint Conference on
  • Conference_Location
    Barcelona
  • ISSN
    1098-7576
  • Print_ISBN
    978-1-4244-6916-1
  • Type

    conf

  • DOI
    10.1109/IJCNN.2010.5596905
  • Filename
    5596905