ISSN : 1796-2048
Volume : 2    Issue : 5    Date : September 2007

A Novel Method for 3D Face Detection and Normalization
Robert Niese, Ayoub Al-Hamadi, and Bernd Michaelis
Page(s): 1-12
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When automatically analyzing images of human faces, either for recognition in biometry
applications or facial expression analysis in human machine interaction, one has to cope with
challenges caused by different head pose, illumination and expression. In this article we propose a
new stereo based method for effectively solving the pose problem through 3D face detection and
normalization. The proposed method applies a model-based matching and is especially intended
for the study of facial features and the description of their dynamic changes in image sequences
under the assumption of non-cooperative persons. In our work, we are currently implementing a
new application to observe and analyze single faces of post-operative patients. In the proposed
method, face detection is based on color driven clustering of 3D points derived from stereo. A mesh
model is matched with the post-processed face cluster using a variant of the Iterative Closest Point
algorithm (ICP). Pose is derived from correspondence. Then, pose and model information is used
for the synthesis of the face normalization. Results show, stereo and color are powerful cues for
finding the face and its pose under a wide range of poses, illuminations and expressions (PIE).
Head orientation may vary in out of plane rotations up to ±45°.

Index Terms
Image and Video Processing, ICP-Matching, Computer Vision, 3D Face Detection, Normalization