• DocumentCode
    1781384
  • Title

    A Fast 3-D Face Reconstruction Method

  • Author

    Changming Meng ; Fan Zhou ; Ruomei Wang

  • Author_Institution
    Sch. of Inf. Sci. & Technol., Sun Yat-sen Univ., Guangzhou, China
  • fYear
    2014
  • fDate
    28-30 Nov. 2014
  • Firstpage
    146
  • Lastpage
    150
  • Abstract
    Plausible human face reconstruction is an active topic of virtual human research and has amounts of achievements. However, most of them require abundant image source and complex manual operations. In this paper, we propose a method for reconstructing 3D face models using only one frontal face image. Six neutral head models of male and female in three human races are used as the prototypes and one of them is selected to be deformed into the particular face every time. Feature points are extracted from frontal image automatically. Then we link the feature points extracted from the 2D image to the points on the 3D model, and deform the model according to the relative position of the feature points using the radial basis function (RBF) algorithm. In order to make the deformed model more realistic, we use face texture restoration and texture mapping technology. The experiments show that this method can quickly and automatically generate a personalized and realistic face model.
  • Keywords
    face recognition; feature extraction; image reconstruction; image restoration; image texture; radial basis function networks; solid modelling; 3D model; RBF algorithm; face texture restoration; fast 3D face reconstruction method; feature points extraction; frontal face image; neutral head models; plausible human face reconstruction; radial basis function algorithm; texture mapping technology; virtual human research; Computational modeling; Deformable models; Face; Feature extraction; Image reconstruction; Solid modeling; Three-dimensional displays;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Digital Home (ICDH), 2014 5th International Conference on
  • Conference_Location
    Guangzhou
  • Print_ISBN
    978-1-4799-4285-5
  • Type

    conf

  • DOI
    10.1109/ICDH.2014.36
  • Filename
    6996751