• DocumentCode
    2964136
  • Title

    Pose invariant face recognition with 3D morphable model and neural network

  • Author

    Choi, Hyun-Chul ; Kim, Sam-Yong ; Oh, Sang-Hoon ; Oh, Se-young ; Cho, Sun-Young

  • Author_Institution
    Dept. of Electron. & Electr. Eng., Pohang Univ. of Sci. & Technol. (POSTECH), Pohang
  • fYear
    2008
  • fDate
    1-8 June 2008
  • Firstpage
    4131
  • Lastpage
    4136
  • Abstract
    This paper introduces a pose invariant face recognition method with a training image and a query image using 3D morphable model and neural network. Our system uses 3D morphable model to get the reconstructed 3D face from the training image and obtains 2D image patches of facial components from the 3D face under varying head pose. The 2D image patches are used to train a neural network for pose invariant face recognition. Because those patches are obtained from the varying head pose, the neural network has robustness in the query image under the different head pose form the training image. Our pose invariant face recognition system has the performance of correct recognition higher than 98% with BJUT 3D scan database.
  • Keywords
    face recognition; image reconstruction; learning (artificial intelligence); neural nets; 3D face reconstruction; 3D morphable model; 3D scan database; neural network; pose invariant face recognition; query image; Face detection; Face recognition; Humans; Image databases; Lighting; Magnetic heads; Neural networks; Robustness; Shape; Spatial databases;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1098-7576
  • Print_ISBN
    978-1-4244-1820-6
  • Electronic_ISBN
    1098-7576
  • Type

    conf

  • DOI
    10.1109/IJCNN.2008.4634393
  • Filename
    4634393