• DocumentCode
    3649282
  • Title

    PCA type algorithm applied in face recognition

  • Author

    Sergiu Nedevschi;Ioan Radu Peter;Adina Mandruţ

  • Author_Institution
    Department of Computer Science, Technical University of Cluj-Napoca, G. Bariţ
  • fYear
    2012
  • Firstpage
    167
  • Lastpage
    171
  • Abstract
    One of the widely used approaches in image recognition is principal component analysis (PCA) because of the good balance between the simplicity and speed of the algorithm and the results obtained by using it. In the last years many variants of PCA were developed: two dimensional PCA, two directional two dimensional PCA, extended two dimensional PCA and extended two dimensional two directional PCA, the last one developed by the first two authors of the present paper. In this paper we go further with this study by considering a mixed approach between E2DPCA and diagonal PCA. The mixed approach not only takes approximately the same amount of time for training and testing as the classical approach, but also gives better recognition accuracy for some of the PCA algorithm variants.
  • Keywords
    "Principal component analysis","Covariance matrix","Face recognition","Training","Symmetric matrices","Databases","Vectors"
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computer Communication and Processing (ICCP), 2012 IEEE International Conference on
  • Print_ISBN
    978-1-4673-2953-8
  • Type

    conf

  • DOI
    10.1109/ICCP.2012.6356181
  • Filename
    6356181