Experiments about the Generalization Ability of Common Vector based Methods for Face Recognition
Marcelo Armengot, Francesc J. Ferri, Wladimiro Díaz
2007
Abstract
This work presents some preliminary results about exploring and proposing new extensions of common vector based subspace methods that have been recently proposed to deal with very high dimensional classification problems. Both the common vector and the discriminant vector approaches are considered. The different dimensionalities of the subspaces that these methods use as intermediate step are considered in different situations and their relation to the generalization ability of each method is analyzed. Comparative experiments using different databases for the face recognition problem are performed to support the main conclusions of the paper.
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Paper Citation
in Harvard Style
Armengot M., J. Ferri F. and Díaz W. (2007). Experiments about the Generalization Ability of Common Vector based Methods for Face Recognition . In Proceedings of the 7th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2007) ISBN 978-972-8865-93-1, pages 129-137. DOI: 10.5220/0002432401290137
in Bibtex Style
@conference{pris07,
author={Marcelo Armengot and Francesc J. Ferri and Wladimiro Díaz},
title={Experiments about the Generalization Ability of Common Vector based Methods for Face Recognition},
booktitle={Proceedings of the 7th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2007)},
year={2007},
pages={129-137},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002432401290137},
isbn={978-972-8865-93-1},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 7th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2007)
TI - Experiments about the Generalization Ability of Common Vector based Methods for Face Recognition
SN - 978-972-8865-93-1
AU - Armengot M.
AU - J. Ferri F.
AU - Díaz W.
PY - 2007
SP - 129
EP - 137
DO - 10.5220/0002432401290137