• DocumentCode
    350783
  • Title

    Automatic face feature tracking

  • Author

    Jin, Kyung-Chan ; Cho, Jin-Ho

  • Author_Institution
    Dept. of Electron. Eng., Kyungpook Nat. Univ., Taegu, South Korea
  • Volume
    1
  • fYear
    1999
  • fDate
    1999
  • Firstpage
    68
  • Abstract
    A reliable face tracking can be obtained by integrating of the region detection, feature locating and tracking. To detect the face feature region, we used the mean shift method that is a clustering technique for multivariate data, and to track face landmark features, we also used the STK tracking method. STK tracking is very efficient for feature tracking, but the Newton-Raphson iteration scheme has the initial coordinate problem for tracking features. To solve the problem, we proposed a new BMA-NR method of the STK algorithm for face landmark features. Preliminary results indicate that this method solves the local minimum problem which occurs by NR iteration
  • Keywords
    Newton-Raphson method; face recognition; feature extraction; tracking; BMA-NR method; Newton-Raphson iteration scheme; STK tracking method; automatic face feature tracking; clustering technique; face landmark features; feature locating; initial coordinate problem; local minimum problem; mean shift method; multivariate data; region detection; Clustering algorithms; Computer vision; Convergence; Equations; Face detection; Feature extraction; Kernel; Reliability engineering; Robustness; Skin;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    TENCON 99. Proceedings of the IEEE Region 10 Conference
  • Conference_Location
    Cheju Island
  • Print_ISBN
    0-7803-5739-6
  • Type

    conf

  • DOI
    10.1109/TENCON.1999.818351
  • Filename
    818351