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Automatic 3D Face Reconstruction from Single Images or Video

MPG-Autoren
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Kim,  KI
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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Kienzle,  W
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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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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Zitation

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.


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