Extension of Robust Principal Component Analysis for Incremental Face Recognition

Haïfa Nakouri, Limam Mohamed

Abstract

Face recognition performance is highly affected by image corruption, shadowing and various face expressions. In this paper, an efficient incremental face recognition algorithm, robust to image occlusion, is proposed. This algorithm is based on robust alignment by sparse and low-rank decomposition for linearly correlated images, extended to be incrementally applied for large face data sets. Based on the latter, incremental robust principal component analysis (PCA) is used to recover the intrinsic data of a sequence of images of one subject. A new similarity metric is defined for face recognition and classification. Experiments on five databases, based on four different criteria, illustrate the efficiency of the proposed method. We show that our method outperforms other existing incremental PCA approaches such as incremental singular value decomposition, add block singular value decomposition and candid covariance-free incremental PCA in terms of recognition rate under occlusions, facial expressions and image perspectives.

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Paper Citation


in Harvard Style

Nakouri H. and Mohamed L. (2013). Extension of Robust Principal Component Analysis for Incremental Face Recognition . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013) ISBN 978-989-8565-47-1, pages 549-555. DOI: 10.5220/0004288305490555


in Bibtex Style

@conference{visapp13,
author={Haïfa Nakouri and Limam Mohamed},
title={Extension of Robust Principal Component Analysis for Incremental Face Recognition},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013)},
year={2013},
pages={549-555},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004288305490555},
isbn={978-989-8565-47-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013)
TI - Extension of Robust Principal Component Analysis for Incremental Face Recognition
SN - 978-989-8565-47-1
AU - Nakouri H.
AU - Mohamed L.
PY - 2013
SP - 549
EP - 555
DO - 10.5220/0004288305490555