• DocumentCode
    2691813
  • Title

    Simplified Nearest Feature Line Space for Face Recognition

  • Author

    Yan, Lijun ; Feng, Qingxiang ; Pan, Jeng-Shyang

  • Author_Institution
    Dept. of Autom. Test & Control, Harbin Inst. of Technol., Harbin, China
  • fYear
    2012
  • fDate
    7-9 July 2012
  • Firstpage
    269
  • Lastpage
    272
  • Abstract
    In this paper, a novel subspace algorithm entitled Simplified Nearest Feature Line Space (SNFLS) is proposed based on Nearest Feature Line (NFL). NFL space (NFLS) is a subspace learning method and has desirable discriminant power. However, the computational complexity of NFLS is too high because all the feature lines are used. In SNFLS algorithm, some feature lines will be chosen for learning. SNFLS has the same discriminant power as NFLS. At the same time, SNFLS has a lower NFLS. Experimental results confirm its efficiency.
  • Keywords
    computational complexity; face recognition; feature extraction; learning (artificial intelligence); SNFLS algorithm; computational complexity; discriminant power; face recognition; simplified nearest feature line space; subspace learning method; Algorithm design and analysis; Computational complexity; Databases; Face; Face recognition; Feature extraction; Training; Face Recognition; Nearest Feature Line; Nearest Feature Line Space;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computing, Measurement, Control and Sensor Network (CMCSN), 2012 International Conference on
  • Conference_Location
    Taiyuan
  • Print_ISBN
    978-1-4673-2033-7
  • Type

    conf

  • DOI
    10.1109/CMCSN.2012.65
  • Filename
    6245864