A Generalized EM Approach for 3D Model Based Face Recognition under Occlusions

Authors:
Michael De Smet;Rik Fransens;Luc Van Gool
Affiliations:
K.U.Leuven ESAT-PSI, Leuven, Belgium;K.U.Leuven ESAT-PSI, Leuven, Belgium;K.U.Leuven ESAT-PSI, Leuven, Belgium
Venue:
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Year:
2006

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Abstract

This paper describes an algorithm for pose and illumination invariant face recognition from a single image under occlusions. The method iteratively estimates the parameters of a 3D morphable face model to approximate the appearance of a face in an image. Simultaneously, a visibility map is computed which segments the image into visible and occluded regions. The visibility map is incorporated into a probabilistic image formation model as a set of spatially correlated random variables. This leads to a Generalized Expectation-Maximization algorithm in which the estimation of the morphable model related parameters is interleaved with visibility computations. The validity of the algorithm is verified by a face recognition experiment using images from the publicly available AR Face Database.