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Diploma Thesis | {Sunkel2006, ... | Diplomarbeit

Sunkel, Martin

Face Detection and 3D Face Reconstruction

Universität des Saarlandes, March, 2006

A fully automated 3D face reconstruction system for faces in 2D images is presented. It is implemented
incorporating a method for facial feature detection into the initialization of the 3D face
reconstruction process provided by Blanz et al.[2][3]. The initialization of that method takes alignments
of previously selected facial feature points with their according vertices in the 3D face model.
Several methods for face detection are presented and discussed. In order to reliably detect facial
features independently of rotation and size of a face, support vector classifiers are applied. Their
data are represented by the gradient of the images used for training.
The training images are generated by using the 3D Morphable Face Model[2]. They are selected in
a database of face images with rotations around the vertical axis that was previously fitted to the
Morphable Model. That enables to select facial features within these images without user interaction.
In order to protect against detection outliers (which would disturb the reconstruction) the feature
points are validated by each other on base of their detected geometric position. On base of the
detection results a heuristic is provided filling up discarded feature points.

Face Detection, Face Reconstruction
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January
2011
Max-Planck-Institut für Informatik
Computer Graphics Group
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BibTeX Entry:
@MASTERSTHESIS{Sunkel2006,
AUTHOR = {Sunkel, Martin},
TITLE = {Face Detection and 3D Face Reconstruction},
SCHOOL = {Universit{\"a}t des Saarlandes},
YEAR = {2006},
TYPE = {Diploma thesis}
MONTH = {March},
}





Entry last modified by Martin Sunkel, 01/25/2011
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Editor(s)
Martin Sunkel
Created
01/25/2011 08:41:04 PM
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Editor
Martin Sunkel



Edit Date
01/25/2011 08:41:09 PM