A Face Recognition Method Based on LBP and GMM
Authors
Yuwen Song, Qingling Zhang, Xiuquan Xia
Corresponding Author
Yuwen Song
Available Online May 2018.
- DOI
- 10.2991/ammsa-18.2018.54How to use a DOI?
- Keywords
- face recognition; LBP; GMM; EM algorithm
- Abstract
This paper proposes a face recognition method based on local binary pattern(LBP) and Gaussian mixture model(GMM). Firstly, combine Uniform Pattern and Rotation Invariant LBP with traditional LBP operator to obtain initial classification data. Then, adopt GMM to classify face textures, and use EM algorithm to estimate the model parameters where K-means method is applied for initialization. Finally, the experiment is carried out on Yale and ORL face database. The results show that the recognition accuracy of this method has been greatly improved comparing with LBP, PCA or PCA+FLDA alone, especially for small samples.
- 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/).
Cite this article
TY - CONF AU - Yuwen Song AU - Qingling Zhang AU - Xiuquan Xia PY - 2018/05 DA - 2018/05 TI - A Face Recognition Method Based on LBP and GMM BT - Proceedings of the 2018 2nd International Conference on Applied Mathematics, Modelling and Statistics Application (AMMSA 2018) PB - Atlantis Press SP - 261 EP - 264 SN - 1951-6851 UR - https://doi.org/10.2991/ammsa-18.2018.54 DO - 10.2991/ammsa-18.2018.54 ID - Song2018/05 ER -