• DocumentCode
    595452
  • Title

    Accelerated robust sparse coding for fast face recognition

  • Author

    Guanglu Liu ; Yan Yanand ; Hanzi Wang

  • Author_Institution
    Sch. of Inf. Sci. & Technol., Xiamen Univ., Xiamen, China
  • fYear
    2012
  • fDate
    11-15 Nov. 2012
  • Firstpage
    3394
  • Lastpage
    3397
  • Abstract
    In this paper, we propose an accelerated robust sparse coding (ARSC) method which is based on the combination of linear-regression based classification and robust sparse coding for fast face recognition. First, linear-regression based classification (LRC) is used to select the candidate face set, which can effectively reduce the search scope. Then, robust sparse coding (RSC) is applied to perform accurate face identification in the selected face set. Extensive experimental results on various face databases demonstrate that the proposed ARSC can greatly reduce the computational complexity while achieving high recognition performance.
  • Keywords
    computational complexity; face recognition; image classification; image coding; regression analysis; search problems; visual databases; ARSC method; LRC; accelerated robust sparse coding method; candidate face set; computational complexity; face databases; face identification; fast face recognition; linear-regression based classification; search scope; Computational complexity; Databases; Encoding; Face; Face recognition; Lighting; Robustness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2012 21st International Conference on
  • Conference_Location
    Tsukuba
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4673-2216-4
  • Type

    conf

  • Filename
    6460893