• DocumentCode
    2847513
  • Title

    3D face sketch modeling and assessment for component based face recognition

  • Author

    Canavan, Shaun ; Xing Zhang ; Yin, Lijun ; Zhang, Yong

  • Author_Institution
    State Univ. of New York at Binghamton, Binghamton, NY, USA
  • fYear
    2011
  • fDate
    11-13 Oct. 2011
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Abstract 3D facial representations have been widely used for face recognition. There has been intensive research on geometric matching and similarity measurement on 3D range data and 3D geometric meshes of individual faces. However, little investigation has been done on geometric measurement for 3D sketch models. In this paper, we study the 3D face recognition from 3D face sketches which are derived from hand-drawn sketches and machine generated sketches. First, we have developed a 3D sketch modeling approach to create 3D facial sketch models from 2D facial sketch images. Second, we compared the 3D sketches to the existing 3D scans. Third, the 3D face similarity is measured between 3D sketches versus 3D scans, and 3D sketches versus 3D sketches based on the spatial Hidden Markov Model (HMM) classification. Experiments are conducted on both the BU-4DFE database and YSU face sketch database, resulting in a recognition rate at around 92% on average.
  • Keywords
    face recognition; hidden Markov models; image matching; visual databases; 2D facial sketch images; 3D face sketch assessment; 3D face sketch modeling; 3D facial representations; 3D geometric meshes; 3D range data; BU-4DFE database; HMM; Hidden Markov Model; YSU face sketch database; face recognition; geometric matching; geometric measurement; hand drawn sketches; Active appearance model; Data models; Face recognition; Hidden Markov models; High definition video; Manuals; Three dimensional displays;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biometrics (IJCB), 2011 International Joint Conference on
  • Conference_Location
    Washington, DC
  • Print_ISBN
    978-1-4577-1358-3
  • Electronic_ISBN
    978-1-4577-1357-6
  • Type

    conf

  • DOI
    10.1109/IJCB.2011.6117501
  • Filename
    6117501