PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Parametric Stereo for Multi-Pose Face Recognition and 3D-Face Modeling
Rik Fransens, Christoph Strecha, Luc Van Gool and Luc Van Gool
In: IEEE International Workshop on Analysis and Modeling of Faces and Gestures, 16 Oct 2005, Beijing, China.

Abstract

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, ranging from a frontal to a profile view. The face recognition results are very good, with 100% recognition on frontal views and 97% recognition on half-profile views.

EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
ID Code:1621
Deposited By:Rik Fransens
Deposited On:28 November 2005