Face to Face: Anthropometry-Based Interactive Face Shape Modeling Using Model Priors
This paper presents a new anthropometrics-based method for generating realistic, controllable face models. Our method establishes an intuitive and efficient interface to facilitate procedures for interactive 3D face modeling and editing. It takes 3D face scans as examples in order to exploit the var...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi Limited
2009-01-01
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| Series: | International Journal of Computer Games Technology |
| Online Access: | http://dx.doi.org/10.1155/2009/573924 |
| Summary: | This paper presents a new anthropometrics-based method
for generating realistic, controllable face models. Our method
establishes an intuitive and efficient interface to facilitate
procedures for interactive 3D face modeling and editing. It
takes 3D face scans as examples in order to exploit the variations
presented in the real faces of individuals. The system
automatically learns a model prior from the data-sets
of example meshes of facial features using principal component
analysis (PCA) and uses it to regulate the naturalness
of synthesized faces. For each facial feature, we compute
a set of anthropometric measurements to parameterize the
example meshes into a measurement space. Using PCA coefficients
as a compact shape representation, we formulate
the face modeling problem in a scattered data interpolation
framework which takes the user-specified anthropometric
parameters as input. Solving the interpolation problem
in a reduced subspace allows us to generate a natural face
shape that satisfies the user-specified constraints. At runtime,
the new face shape can be generated at an interactive
rate. We demonstrate the utility of our method by presenting
several applications, including analysis of facial features
of subjects in different race groups, facial feature transfer,
and adapting face models to a particular population group. |
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| ISSN: | 1687-7047 1687-7055 |