A Generalized EM Approach for 3D Model Based Face Recognition Under Occlusions
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.
Cite
Text
De Smet et al. "A Generalized EM Approach for 3D Model Based Face Recognition Under Occlusions." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2006. doi:10.1109/CVPR.2006.26Markdown
[De Smet et al. "A Generalized EM Approach for 3D Model Based Face Recognition Under Occlusions." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2006.](https://mlanthology.org/cvpr/2006/smet2006cvpr-generalized/) doi:10.1109/CVPR.2006.26BibTeX
@inproceedings{smet2006cvpr-generalized,
title = {{A Generalized EM Approach for 3D Model Based Face Recognition Under Occlusions}},
author = {De Smet, Michaël and Fransens, Rik and Van Gool, Luc},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {2006},
pages = {1423-1430},
doi = {10.1109/CVPR.2006.26},
url = {https://mlanthology.org/cvpr/2006/smet2006cvpr-generalized/}
}