An Ensemble Method of Global and Local Representation for Face Recognition

DOI

10.2991/acaai-18.2018.23How to use a DOI?

Keywords

face recognition; Shearlets transform; deep convolution; PCA; ensemble

Abstract

To aim at the challenge of face recognition to uncontrolled situations, an ensemble method of global and local representation for face recognition is presented in this paper. shearlets transform is firstly employed to decompose a image into subimages. Then directional information is utilized along with conventional scaling and translation parameters, global feature of a face image is extracted by principle component analysis. Thirdly, local feature of a face image is extracted by a deep convolutional neural network. Finally, an ensemble of global and local feature is performed by weighted score. Experimental results on two challenge face databases show that the proposed method achieved higher face recognition accuracy than art-of-the-state methods. Hence, the ensemble of global and local feature is more potential features for the design of efficient face recognition system.

Copyright

© 2018, 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  - Zhiyong Zeng
PY  - 2018/03
DA  - 2018/03
TI  - An Ensemble Method of Global and Local Representation for Face Recognition
BT  - Proceedings of the 2018 International Conference on Advanced Control, Automation and Artificial Intelligence (ACAAI 2018)
PB  - Atlantis Press
SP  - 94
EP  - 100
SN  - 1951-6851
UR  - https://doi.org/10.2991/acaai-18.2018.23
DO  - 10.2991/acaai-18.2018.23
ID  - Zeng2018/03
ER  -