• DocumentCode
    2605490
  • Title

    Face Detection in Complex Background Using AdaBoost Algorithm

  • Author

    Guanglei Sheng ; Wenze Li

  • Author_Institution
    Zhengzhou Shengda Coll. of Econ.&Trade Manage., Zhengzhou, China
  • fYear
    2012
  • fDate
    21-23 April 2012
  • Firstpage
    149
  • Lastpage
    154
  • Abstract
    This paper has studied one kind based on rectangle features face detection technology. The first use of a fixed size training set training out of each rectangle features corresponding to the weak classifier, the weak classifier selection, made some improvement. Using AdaBoost algorithm to train the weak classifier, we get a strong classifier. In the end, we make strong classifier construction into a cascade structure of a human face detector, the experimental results show that the detector can quickly and accurately detect the human face images.
  • Keywords
    face recognition; feature extraction; image classification; learning (artificial intelligence); object detection; AdaBoost algorithm; complex background; face detection; fixed size training set; human face detector; rectangle features; weak classifier selection; Classification algorithms; Face; Face detection; Feature extraction; Humans; Pattern recognition; Training; face detection; integral image; rectangle feature; skin color segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Internet Computing for Science and Engineering (ICICSE), 2012 Sixth International Conference on
  • Conference_Location
    Henan
  • Print_ISBN
    978-1-4673-1683-5
  • Type

    conf

  • DOI
    10.1109/ICICSE.2012.23
  • Filename
    6239738