• DocumentCode
    1660843
  • Title

    Multi-Component/Multi-Model AAM framework for face image modeling

  • Author

    Khan, Muhammad Asad ; Xydeas, Costas ; Ahmed, Hameeza

  • Author_Institution
    Infolab21, Lancaster Univ., Lancaster, UK
  • fYear
    2013
  • Firstpage
    2124
  • Lastpage
    2128
  • Abstract
    An image face modeling framework is proposed that aims to enhance the face modeling capability of the well known Active Appearance Model (AAM). AAM has been used successfully in person-specific related applications but it poses significant limitations when employed in generic face modeling. Thus this work is focused on the development of new face models which are generic in nature and which accurately fit unseen image faces, both in terms of shape and texture. For this purpose, images are decomposed into face related components which are subsequently clustered on the basis of shape similarities. Experimental results show that models generated through this novel framework can be significantly more effective than conventional AAM, in terms of both shape and texture.
  • Keywords
    face recognition; image texture; active appearance model; face image modeling; image shape; image texture; multicomponent-multimodel AAM framework; Abstracts; Active appearance model; Biomedical imaging; Computational modeling; Educational institutions; Active Appearance Models; Image Face Analysis and Synthesis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on
  • Conference_Location
    Vancouver, BC
  • ISSN
    1520-6149
  • Type

    conf

  • DOI
    10.1109/ICASSP.2013.6638029
  • Filename
    6638029