• DocumentCode
    495462
  • Title

    Affine Subspace Nearest Points Classification Algorithm for Wavelet Face Recognition

  • Author

    Xiaofei, Zhou ; Yong, Shi

  • Author_Institution
    Res. Center on Fictitious Econ. & Data Sci., Chinese Acad. of Sci., Beijing, China
  • Volume
    3
  • fYear
    2009
  • fDate
    March 31 2009-April 2 2009
  • Firstpage
    684
  • Lastpage
    688
  • Abstract
    A new classification method called affine subspace nearest points (ASNP) algorithm is presented in this paper. Similar to the idea of the geometrical explanation of support vector machines (SVMs), the ASNP algorithm designed by us as a binary classifier extends the areas searched for the nearest points from the convex hulls in SVM to affine subspaces, and constructs the decision hyperplane separating the affine subspaces with equivalent margin. We combine the algorithm with the 2D wavelet transform (WT) for face recognition. The low frequency features of face images extracted by 2D wavelet transform are employed as the inputs of the ASNP classifiers. Experiments on the ORL face database show that the proposed method obtains good recognition accuracy.
  • Keywords
    data mining; face recognition; image classification; support vector machines; visual databases; wavelet transforms; 2D wavelet transform; ORL face database; SVM; affine subspace nearest points classification algorithm; binary classifier; feature extraction; support vector machines; wavelet face recognition; Classification algorithms; Computer science; Data mining; Face recognition; Frequency; Image databases; Spatial databases; Support vector machine classification; Support vector machines; Wavelet transforms; SVM; affine subspace; classification; data mining; face recognition.; recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Information Engineering, 2009 WRI World Congress on
  • Conference_Location
    Los Angeles, CA
  • Print_ISBN
    978-0-7695-3507-4
  • Type

    conf

  • DOI
    10.1109/CSIE.2009.191
  • Filename
    5170928