PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

A Generalized EM Approach for 3D Model Based Face Recognition under Occlusions
Michael De Smet, Rik Fransens, Luc Van Gool and Luc Van Gool
In: IEEE Conference on Computer Vision and Pattern Recognition, 17-22 June 2006, New York, USA.


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.

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EPrint Type:Conference or Workshop Item (Poster)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
ID Code:2179
Deposited By:Rik Fransens
Deposited On:18 August 2006