Hierarchical Morphable Models

نویسندگان

  • Michael J. Jones
  • Tomaso A. Poggio
چکیده

This paper presents a new technique for modelling object classes (such as faces) and matching the model to novel images from the object class. The technique can be used for a variety of image analysis applications including face recognition, object veri cation and facial expression analysis. The model, called a hierarchical morphable model, is \learned" from example images (partioned into components) and their correspondences. This is an extension to the work on morphable models described in previous papers ([6], [5], [12]). Hierarchical morphable models are shown to nd good matches to novel face images and are also robust to partial occlusion.

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تاریخ انتشار 1998