MURAL - Maynooth University Research Archive Library

    Facial expression synthesis using a statistical model of appearance

    Ghent, John and McDonald, John (2004) Facial expression synthesis using a statistical model of appearance. In: The IASTED International Conference on Visualization, Imaging, and Image Processing (VIIP 2004), September 6-8, 2004, Marbella, Spain.

    Download (873kB) | Preview

    Share your research

    Twitter Facebook LinkedIn GooglePlus Email more...

    Add this article to your Mendeley library


    This paper details a procedure for generating a mapping function which maps an image of a neutral face to one depicting a smile. This is achieved by the computation of the Facial Expression Shape Model (FESM) and the Facial Expression Texture Model (FETM). These are statistical models of facial expression based on anatomical analysis of facial expression called the Facial Action Coding System (FACS). The FEAM and the FETM allow for the generation of a subject independent mapping function. These models provide a robust means for upholding the rules of the FACS and are flexible enough to describe subjects that are not present during the training phase. We use these models in conjunction with several Artif icial Neural Networks (ANN) to generate photo-realistic images of facial expressions.

    Item Type: Conference or Workshop Item (Paper)
    Keywords: Image Processing and Analysis; Image Synthesis; Facial Expression Shape Model (FESM); Facial Expression Texture Model (FETM);
    Academic Unit: Faculty of Science and Engineering > Computer Science
    Item ID: 8306
    Depositing User: John McDonald
    Date Deposited: 12 Jun 2017 14:58
    Publisher: ACTA Press
    Refereed: Yes
      Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

      Repository Staff Only(login required)

      View Item Item control page


      Downloads per month over past year

      Origin of downloads