Improving the Dictionary Construction in Sparse Representation using PCANet for Face Recognition

Peiyu Kang, Yonggang Lu, Diqi Pan, Wenjie Guo

Abstract

Recently, sparse representation has attracted increasing interest in computer vision. Sparse representation based methods, such as sparse representation classification (SRC), have produced promising results in face recognition, while the dictionary used for sparse representation plays a key role in it. How to improve the dictionary construction in sparse representation is still an open question. Principal component analysis network (PCANet), as a newly proposed deep learning method, has the advantage of simple network architecture and competitive performance for feature learning. In this paper, we have studied how to use the PCANet to improve the dictionary construction in sparse representation, and proposed a new method for face recognition. The PCANet is used to learn new features from face images, and the learned features are used as dictionary atoms to code the query face images, and then the reconstruction errors after sparse coding are used to classify the face images. It is shown that the proposed method can achieve better performance than the other five state-of-art methods for face recognition.

Download


Paper Citation


in Harvard Style

Kang P., Lu Y., Pan D. and Guo W. (2019). Improving the Dictionary Construction in Sparse Representation using PCANet for Face Recognition.In Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-351-3, pages 517-523. DOI: 10.5220/0007368105170523


in Bibtex Style

@conference{icpram19,
author={Peiyu Kang and Yonggang Lu and Diqi Pan and Wenjie Guo},
title={Improving the Dictionary Construction in Sparse Representation using PCANet for Face Recognition},
booktitle={Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2019},
pages={517-523},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007368105170523},
isbn={978-989-758-351-3},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Improving the Dictionary Construction in Sparse Representation using PCANet for Face Recognition
SN - 978-989-758-351-3
AU - Kang P.
AU - Lu Y.
AU - Pan D.
AU - Guo W.
PY - 2019
SP - 517
EP - 523
DO - 10.5220/0007368105170523