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

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A Generalized EM Approach for 3D Model Based Face Recognition under Occlusions
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.
Michael De Smet, Rik Fransens, Luc J. Van Gool
Added 10 Jun 2010
Updated 10 Jun 2010
Type Conference
Year 2006
Where CVPR
Authors Michael De Smet, Rik Fransens, Luc J. Van Gool
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