In this paper, a new technique for modeling textured 3D faces is introduced. 3D faces can either be
generated automatically from one or more photographs, or modeled directly through an intuitive user
interface. Users are assisted in two key problems of computer aided face modeling. First, new face images
or new 3D face models can be registered automatically by computing dense one-to-one correspondence to
an internal face model. Second, the approach regulates the naturalness of modeled faces avoiding faces
with an ``unlikely'' appearance.
Starting from an example set of 3D face models, we derive a Morphable Face Model by transforming the
shape and texture of the examples into a vector space representation. New faces and expressions can be
modeled by forming linear combinations of the prototypes. Shape and texture constraints derived from the
statistics of our example faces are used to guide manual modeling or automated matching algorithms.
In this framework, it is easy to control complex facial attributes, such as gender, attractiveness, body
weight, or facial expressions. Attributes are automatically learned from a set of faces rated by the user, and
can then be applied to classify and manipulate new faces.
Given a single photograph of a face, we can estimate its 3D shape, its orientation in space and the
illumination conditions in the scene. Starting from a rough estimate of size, orientation and illumination,
our algorithm optimizes these parameters along with the face's internal shape and surface colour to find
the best match to the input image. The face model extracted from the image can be rotated and
manipulated in 3D.