• DocumentCode
    1947461
  • Title

    A new face descriptor using local un-quantized patterns

  • Author

    Mariappan, V.V. ; Jadhav, R.A. ; Sharma, P.B.

  • Author_Institution
    2012 Labs., Huawei, Bangalore, India
  • fYear
    2013
  • fDate
    7-8 Feb. 2013
  • Firstpage
    318
  • Lastpage
    321
  • Abstract
    We present a novel face representation based on local un-quantized patterns (LUP) descriptors. LUP descriptor is a simple yet powerful descriptor which measures the difference of intensities between surrounding pixel with the center in a local neighborhood, but preserves the finer local geometric structure unlike LBP, SIFT or HOG (which uses either the quantized version of local gray level patterns or quantized codes of image gradients). This descriptor also solves the problem of limited spatial support of LBP like operators, where increasing the size of local-neighborhood increases the histogram dimensions exponentially making it unsuitable for real-time needs. By applying principal component analysis (PCA) to LUP, we develop a new srepresentation, which gives better performance than LBP and comparable performance to LARK while only taking a fraction of the computation when compared to the latter.
  • Keywords
    face recognition; image classification; image representation; principal component analysis; LBP like operators; LUP descriptors; PCA; face descriptor; face representation; geometric structure; histogram dimensions; local unquantized patterns; principal component analysis; Computer vision; Face; Face recognition; Histograms; Principal component analysis; Training; Face verification; local binary patterns (LBP); locally adaptive regression kernels (LARK);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing Image Processing & Pattern Recognition (ICSIPR), 2013 International Conference on
  • Conference_Location
    Coimbatore
  • Print_ISBN
    978-1-4673-4861-4
  • Type

    conf

  • DOI
    10.1109/ICSIPR.2013.6497948
  • Filename
    6497948