• DocumentCode
    178134
  • Title

    A Lighting Robust Fitting Approach of 3D Morphable Model Using Spherical Harmonic Illumination

  • Author

    Mingyang Ma ; Xiyuan Hu ; Yuquan Xu ; Silong Peng

  • Author_Institution
    Insititute of Autom., Beijing, China
  • fYear
    2014
  • fDate
    24-28 Aug. 2014
  • Firstpage
    2101
  • Lastpage
    2106
  • Abstract
    3D morph able model (3DMM) is a powerful tool to recover 3D shape and texture from a single facial image. Its foundation consists of three models (i.e. face, camera, and illumination) which can simulate the formulation process of facial images. In this paper, we adopt a new illumination model, the Sphere Harmonic Illumination Model (SHIM), to the 3DMM fitting process. The new illumination model takes more lighting factors into consideration than the Phong´s model. Then, we use a new optimization algorithm to optimize the shape and texture parameters simultaneously under SHIM. Compared with the the existing methods that used SHIM to recover only texture, both the shape and texture recovered by our algorithm are improved. The experiments on he CMU-PIE database also show that, compared to other state-of-the-art methods based on the Phong´s model, the proposed approach enhances the robustness of the fitting of 3DMM against lighting variations.
  • Keywords
    curve fitting; face recognition; image texture; lighting; shape recognition; solid modelling; 3D morphable model; 3D shape recovery; 3D texture recovery; 3DMM fitting process; CMU-PIE database; Phong model; SHIM; facial image formulation process simulation; lighting robust fitting approach; lighting variations; shape parameter optimization; sphere harmonic illumination model; texture parameter optimization; Cameras; Cost function; Face; Lighting; Shape; Three-dimensional displays;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2014 22nd International Conference on
  • Conference_Location
    Stockholm
  • ISSN
    1051-4651
  • Type

    conf

  • DOI
    10.1109/ICPR.2014.366
  • Filename
    6977078