Face recognition in presence of either occlusions, illumination changes or large expression variations is still an open problem. This paper addresses this issue presenting a new local-based face recognition system that combines weak classifiers yielding a strong one. The method relies on sparse approximation using dictionaries built on a pool of local features extracted from automatically cropped images. Experiments on the AR database show the effectiveness of our method, which outperforms current state-of-the art techniques.

Face recognition in uncontrolled conditions using sparse representation and local features / A. Adamo, G. Grossi, R. Lanzarotti (LECTURE NOTES IN COMPUTER SCIENCE). - In: Image analysis and processing – ICIAP 2013 / [a cura di] A. Petrosino. - Heidelberg : Springer, 2013 Sep. - ISBN 9783642411830. - pp. 31-40 (( Intervento presentato al 17. convegno International Conference on Image Analysis and Processing tenutosi a Napoli nel 2013.

Face recognition in uncontrolled conditions using sparse representation and local features

G. Grossi
Primo
;
R. Lanzarotti
2013

Abstract

Face recognition in presence of either occlusions, illumination changes or large expression variations is still an open problem. This paper addresses this issue presenting a new local-based face recognition system that combines weak classifiers yielding a strong one. The method relies on sparse approximation using dictionaries built on a pool of local features extracted from automatically cropped images. Experiments on the AR database show the effectiveness of our method, which outperforms current state-of-the art techniques.
Sparse representation; face recognition; face partial occlusions; expression variations; illumination variations; local features
Settore INF/01 - Informatica
Settore ING-INF/05 - Sistemi di Elaborazione delle Informazioni
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/230236
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