Face Recognition Algorithm Based on Kernel Collaborative Representation

DOI

10.2991/iccia.2012.26How to use a DOI?

Keywords

Face Recognition, KPCA, CRC, Illumination Problem, Occlusion Problem

Abstract

Aiming at solving the problems of occlusion and illumination in face recognition, a new method of face recognition based on Kernel Principal Components Analysis (KPCA) and Collaborative Representation Classifier (CRC) is developed. The KPCA can obtain effective discriminative information and reduce the feature dimensions by extracting face’s nonlinear structures features, the decisive factor. Considering the collaboration among the samples, the CRC which synthetically consider the relationship among samples is used. Experimental results demonstrate that the algorithm obtains good recognition rates and also improves the efficiency. The KCRC algorithm can effectively solve the problem of illumination and occlusion in face recognition.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Liang Zhang
AU  - Jiwen Dong
PY  - 2014/05
DA  - 2014/05
TI  - Face Recognition Algorithm Based on Kernel Collaborative Representation
BT  - Proceedings of the 2012 2nd International Conference on Computer and Information Application (ICCIA 2012)
PB  - Atlantis Press
SP  - 109
EP  - 112
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccia.2012.26
DO  - 10.2991/iccia.2012.26
ID  - Zhang2014/05
ER  -