Automatic 3D Face Reconstruction from Single Images or Video

Breuer, P; Kim, KI; Kienzle, W; Schölkopf, B; Blanz, V

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会議論文

Automatic 3D Face Reconstruction from Single Images or Video

MPS-Authors

/persons/resource/persons84014

Kim, KI
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

/persons/resource/persons84012

Kienzle, W
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

/persons/resource/persons84193

Schölkopf, B
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4813339
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引用

Breuer, P., Kim, K., Kienzle, W., Schölkopf, B., & Blanz, V. (2008). Automatic 3D Face Reconstruction from Single Images or Video. In 2008 8th IEEE International Conference on Automatic Face & Gesture Recognition (pp. 1-8). Piscataway, NJ, USA: IEEE.

引用: https://hdl.handle.net/11858/00-001M-0000-0013-C72D-7

要旨

This paper presents a fully automated algorithm for reconstructing
a textured 3D model of a face from a single
photograph or a raw video stream. The algorithm is based
on a combination of Support Vector Machines (SVMs) and
a Morphable Model of 3D faces. After SVM face detection,
individual facial features are detected using a novel
regression- and classification-based approach, and probabilistically
plausible configurations of features are selected
to produce a list of candidates for several facial feature positions.
In the next step, the configurations of feature points
are evaluated using a novel criterion that is based on a
Morphable Model and a combination of linear projections.
To make the algorithm robust with respect to head orientation,
this process is iterated while the estimate of pose is
refined. Finally, the feature points initialize a model-fitting
procedure of the Morphable Model. The result is a highresolution
3D surface model.