Sparse l2-norm Regularized Regression for Face Recognition

Ahmad J. Qudaimat; Hasan Demirel

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Paper

Sparse l2-norm Regularized Regression for Face Recognition

Topics: Advanced Learning Methods; Classification and Clustering; Machine Learning Methods

In Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods ICPRAM - Volume 1, 453-458, 2019 , Prague, Czech Republic

Authors: Ahmad J. Qudaimat ¹ and Hasan Demirel ²

Affiliations: ¹ Electrical Engineering Departement, Palestine Polytechnic University (PPU), Hebron, Palestine, Electrical and Electronic Engineering Department, Eastern Mediterranean University (EMU), Famagusta and North Cyprus ; ² Electrical and Electronic Engineering Department, Eastern Mediterranean University (EMU), Famagusta and North Cyprus

Keyword(s): Sparsifying Transform, Face Recognition, Dictionary Learning, Transform Learning.

Abstract: In this paper, a new `2-norm regularized regression based face recognition method is proposed, with `0-norm constraint to ensure sparse projection. The proposed method aims to create a transformation matrix that transform the images to sparse vectors with positions of nonzero coefficients depending on the image class. The classification of a new image is a simple process that only depends on calculating the norm of vectors to decide the class of the image. The experimental results on benchmark face databases show that the new method is comparable and sometimes superior to alternative projection based methods published in the field of face recognition.

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Paper citation in several formats:

Qudaimat, A. and Demirel, H. (2019). Sparse l2-norm Regularized Regression for Face Recognition. In Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-351-3; ISSN 2184-4313, SciTePress, pages 453-458. DOI: 10.5220/0007355104530458

@conference{icpram19,
author={Ahmad J. Qudaimat. and Hasan Demirel.},
title={Sparse l2-norm Regularized Regression for Face Recognition},
booktitle={Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2019},
pages={453-458},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007355104530458},
isbn={978-989-758-351-3},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Sparse l2-norm Regularized Regression for Face Recognition
SN - 978-989-758-351-3
IS - 2184-4313
AU - Qudaimat, A.
AU - Demirel, H.
PY - 2019
SP - 453
EP - 458
DO - 10.5220/0007355104530458
PB - SciTePress