• DocumentCode
    3242435
  • Title

    Two Dimension Locally Principal Component Analysis for Face Recognition

  • Author

    Lin, Yu-sheng ; Wang, Jian-guo ; Yang, Jing-Yu

  • Author_Institution
    Dept. of Comput. Sci., Nanjing Univ. of Sci. & Technol., Nanjing
  • fYear
    2008
  • fDate
    22-24 Oct. 2008
  • Firstpage
    1
  • Lastpage
    3
  • Abstract
    In this paper, we propose a feature extraction method called two dimension locally principal component analysis (2DLPCA) for face recognition, which is based directly image matrix rather than 1D image vectors. 2DLPCA seeks to discover the intrinsic image local structure. This local structure may contain useful information for discrimination. Experimental results on ORL face database show the effectiveness of the proposed algorithm.
  • Keywords
    face recognition; feature extraction; matrix algebra; principal component analysis; 2D locally principal component analysis; ORL face database; face recognition; feature extraction; image local structure; image matrix; Computer science; Computer science education; Educational institutions; Electronic mail; Face detection; Face recognition; Feature extraction; Image databases; Principal component analysis; Spatial databases;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2008. CCPR '08. Chinese Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-2316-3
  • Type

    conf

  • DOI
    10.1109/CCPR.2008.52
  • Filename
    4663005
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3242435