• DocumentCode
    2094504
  • Title

    Human Face Feature Extraction and Recognition Base on SIFT

  • Author

    Yanbin, Han ; Jianqin, Yin ; Jinping, Li

  • Author_Institution
    Sch. of Inf. Sci. & Eng., Univ. of Jinan, Jinan, China
  • Volume
    1
  • fYear
    2008
  • fDate
    20-22 Dec. 2008
  • Firstpage
    719
  • Lastpage
    722
  • Abstract
    An important algorithm SIFT, which has been successfully applied in image matching, is employed in face recognition. Firstly, the main region of a face is detected from background images by AdaBoost. Secondly, face features are extracted by using SIFT. Then, face recognition is conducted by the comparing real extracted features with training sets. Experiment shows that, in the ORAL face DB, this scheme can reserve the advantages of SIFT, and have a high robustness in face description.
  • Keywords
    face recognition; feature extraction; image matching; message authentication; transforms; AdaBoost; ORAL face DB; SIFT; human face feature extraction; human face recognition; image matching; scale invariant feature transform; Convolution; Face detection; Face recognition; Feature extraction; Humans; Image databases; Image matching; Image recognition; Principal component analysis; Robustness; AdaBoost; SIFT; face recognition; image match;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Computational Technology, 2008. ISCSCT '08. International Symposium on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-3746-7
  • Type

    conf

  • DOI
    10.1109/ISCSCT.2008.249
  • Filename
    4731527
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2094504