• DocumentCode
    2866021
  • Title

    The Study and Implementation of Face Recognition and Tracking System

  • Author

    Chen, Kai ; Le Jun Zhao

  • Author_Institution
    East China Univ. of Sci. & Technol., Shanghai, China
  • fYear
    2009
  • fDate
    11-13 Dec. 2009
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    There´s some very important meaning in the study of realtime face recognition and tracking system for the video monitoring and artificial vision. The current method is still very susceptible to the illumination condition, non-real time and very common to fail to track the target face especially when partly covered or moving fast. In this paper, we propose to use boosted cascade combined with skin model for face detection and then in order to recognize the candidate faces ,they will be analyzed by the hybrid Wavelet, PCA and SVM method. After that, Meanshift and Kalman filter will be invoked to track the face. The experimental results show that the algorithm has quite good performance in terms of real-time and accuracy.
  • Keywords
    Kalman filters; computer vision; face recognition; principal component analysis; real-time systems; support vector machines; target tracking; video signal processing; wavelet transforms; Kalman filter; PCA; SVM method; artificial vision; boosted cascade; face detection; hybrid wavelet; illumination condition; meanshift; realtime face recognition; skin model; tracking system; video monitoring; Discrete wavelet transforms; Face detection; Face recognition; Filters; Principal component analysis; Signal processing algorithms; Skin; Support vector machines; Target tracking; Wavelet analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-4507-3
  • Electronic_ISBN
    978-1-4244-4507-3
  • Type

    conf

  • DOI
    10.1109/CISE.2009.5366352
  • Filename
    5366352