• DocumentCode
    1720547
  • Title

    Eye detection based on improved ad AdaBoost algorithm

  • Author

    Xiang, Benke ; Cheng, Xiaoping

  • Author_Institution
    Coll. of Comput. & Inf. Sci., Southwest Univ., Chongqing, China
  • Volume
    2
  • fYear
    2010
  • Abstract
    Eye detection is an important step in eye tracking and eye state recognition. An improved AD AdaBoost algorithm for eye detection is proposed to slow the degradation in training step. Weight on negative samples which are classified correctly is released then the other samples´ weight is normalized to slow the expansion of weight on difficult samples. The experiment results show that the approach proposed is real time and has a higher detection accuracy.
  • Keywords
    eye; iris recognition; learning (artificial intelligence); AD AdaBoost algorithm; eye detection; eye state recognition; Classification algorithms; Computers; Degradation; Error analysis; Humans; Signal processing algorithms; Training; AD AdaBoost; Cascaded Classifier; Eye Detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing Systems (ICSPS), 2010 2nd International Conference on
  • Conference_Location
    Dalian
  • Print_ISBN
    978-1-4244-6892-8
  • Electronic_ISBN
    978-1-4244-6893-5
  • Type

    conf

  • DOI
    10.1109/ICSPS.2010.5555731
  • Filename
    5555731
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1720547