Parametric Stereo for Multi-pose Face Recognition and 3D-Face Modeling

This paper presents a new method for face modeling and face recognition from a pair of calibrated stereo cameras. In a first step, the algorithm builds a stereo reconstruction of the face by adjusting the global transformation parameters and the shape parameters of a 3D morphable face model. The adjustment of the parameters is such that stereo correspondence between both images is established, i.e. such that the 3D-vertices of the model project on similarly colored pixels in both images. In a second step, the texture information is extracted from the image pair and represented in the texture space of the morphable face model. The resulting shape and texture coefficients form a person specific feature vector and face recognition is performed by comparing query vectors with stored vectors. To validate our algorithm, an extensive image database was built. It consists of stereo-pairs of 70 subjects. For recognition testing, the subjects were recorded under 6 different head directions, ...

• Type: Conference
• Year: 2005
• Where: AMFG
• Authors: Rik Fransens, Christoph Strecha, Luc J. Van Gool
• Keywords: AMFG 2005, Biometrics, Face Modeling, Face Recognition, Morphable Face Model