• DocumentCode
    2610299
  • Title

    Automated Face Pose Estimation Using Elastic Energy Models

  • Author

    Zhao, Sanqiang ; Gao, Yongsheng

  • Author_Institution
    Sch. of Eng., Griffith Univ., Brisbane, Qld.
  • Volume
    4
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    618
  • Lastpage
    621
  • Abstract
    Face pose estimation forms an important part in a face recognition system. However, fully automated and accurate pose determination still remains an unsolved problem in the research community. In this paper, we propose a novel elastic energy model to automatically estimate face poses. Our method employs statistical energy contributions of a set of feature points, which can avoid over-trusting selected anchor points. It provides a robust solution to the feature localisation inaccuracy problem, which is inevitable in practical applications with cluttered backgrounds. As a general configuration, our model can be easily implemented and extended to other non-rigid objects. Its effectiveness and robustness are revealed in our experiments
  • Keywords
    face recognition; feature extraction; statistical analysis; elastic energy models; face pose estimation; face recognition system; feature localisation; feature points; nonrigid objects; pose determination; statistical energy; Active shape model; Application software; Computer vision; Context modeling; Face detection; Face recognition; Image restoration; Power engineering and energy; Robustness; Springs;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-2521-0
  • Type

    conf

  • DOI
    10.1109/ICPR.2006.291
  • Filename
    1699917