• DocumentCode
    3324395
  • Title

    Face recognition from one example view

  • Author

    Beymer, David ; Poggio, Tomaso

  • Author_Institution
    Artificial Intelligence Lab., MIT, Cambridge, MA, USA
  • fYear
    1995
  • fDate
    20-23 Jun 1995
  • Firstpage
    500
  • Lastpage
    507
  • Abstract
    To create a pose-invariant face recognizer, one strategy is the view-based approach, which uses a set of real example views at different poses. But what if we only have one real view available, such as a scanned passport photo-can we still recognize faces under different poses? Given one real view at a known pose, it is still possible to use the view-based approach by exploiting prior knowledge of faces to generate virtual views, or views of the face as seen from different poses. To represent prior knowledge, we use 2D example views of prototype faces under different rotations. We develop example-based techniques for applying the rotation seen in the prototypes to essentially “rotate” the single real view which is available. Next, the combined set of one real and multiple virtual views is used as example views for a view-based, pose-invariant face recognizer. Oar experiments suggest that among the techniques for expressing prior knowledge of faces, 2D example-based approaches should be considered alongside the more standard 3D modeling techniques
  • Keywords
    face recognition; image recognition; motion estimation; 2D example views; 3D modeling techniques; example-based techniques; face recognition; pose-invariant face recognizer; prototype faces; view-based approach; Artificial intelligence; Biology computing; Computer graphics; Face detection; Face recognition; Humans; Laboratories; Learning; Lighting; Prototypes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision, 1995. Proceedings., Fifth International Conference on
  • Conference_Location
    Cambridge, MA
  • Print_ISBN
    0-8186-7042-8
  • Type

    conf

  • DOI
    10.1109/ICCV.1995.466898
  • Filename
    466898