Face Recognition Algorithm Based on Kernel Collaborative Representation
Liang Zhang, Jiwen Dong
Available Online May 2014.
- 10.2991/iccia.2012.26How to use a DOI?
- Face Recognition, KPCA, CRC, Illumination Problem, Occlusion Problem
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.
- © 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/).
Cite this article
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 -