• DocumentCode
    615100
  • Title

    Deformable face ensemble alignment with robust grouped-L1 anchors

  • Author

    Xin Cheng ; Fookes, Clinton ; Sridharan, Sridha ; Saragih, Jason ; Lucey, Simon

  • Author_Institution
    Queensland Univ. of Technol., Brisbane, QLD, Australia
  • fYear
    2013
  • fDate
    22-26 April 2013
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    Many methods exist at the moment for deformable face fitting. A drawback to nearly all these approaches is that they are (i) noisy in terms of landmark positions, and (ii) the noise is biased across frames (i.e. the misalignment is toward common directions across all frames). In this paper we propose a grouped L1-norm anchored method for simultaneously aligning an ensemble of deformable face images stemming from the same subject, given noisy heterogeneous landmark estimates. Impressive alignment performance improvement and refinement is obtained using very weak initialization as “anchors”.
  • Keywords
    face recognition; alignment performance improvement; deformable face ensemble alignment; grouped L1-norm anchored method; landmark positions; noisy heterogeneous landmark; Active appearance model; Databases; Face; Noise measurement; Robustness; Shape; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automatic Face and Gesture Recognition (FG), 2013 10th IEEE International Conference and Workshops on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4673-5545-2
  • Electronic_ISBN
    978-1-4673-5544-5
  • Type

    conf

  • DOI
    10.1109/FG.2013.6553739
  • Filename
    6553739