Fusion of Local and Global Features Using Multiple Kernel Learning for Face Recognition
YANG Sai1, ZHAO Chun-xia2, LIU Fan3
1. School of Electrical Engineering, Nantong University, Nantong, Jiangsu 226019, China;
2. School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, China;
3. College of Computer and Information, Hohai University, Nanjing, Jiangsu 210098, China
A new face recognition algorithm via bag-of-words(BoW) is proposed.In specific,it uses BoW and the global pattern of BoW respectively as the local feature and global feature of face images.Multiple kernel learning is adopted to fuse the local and global features.Extensive experiments were carried out on four face databases,i.e.AR,FERET,CMU PIE and LFW.The results show that our method can effectively solve the small training size problem and is more robust to expression changes,position variations and occlusion.
杨赛, 赵春霞, 刘凡. 多核学习融合局部和全局特征的人脸识别算法[J]. 电子学报, 2016, 44(10): 2344-2350.
YANG Sai, ZHAO Chun-xia, LIU Fan. Fusion of Local and Global Features Using Multiple Kernel Learning for Face Recognition. Acta Electronica Sinica, 2016, 44(10): 2344-2350.
[1] Lai Z H,Xu Y,Chen Q C,Yang J.Multilinear sparse principal component analysis[J].IEEE Transactions on Neural Networks and Learning Systems,2014,25(10):1942-1950.
[2] Wang H X,Lu X S,Zheng W N.Fisher discriminant analysis with L1-norm[J].IEEE Transactions on Cybernetics,2013,44(6):828-842.
[3] Wright J,Yang AY,Ganesh A,Satry S S,Ma Y.Robust face recognition via sparse representation[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2009,31(2):210-226.
[4] Zhang L,Yang M,Feng X C.Sparse representation or collaborative representation:which helps face recognition[A]? Proceedings of the 13th IEEE International Conference on Computer Vision[C].Barcelona,Spain:IEEE Computer Society,2011.471-478.
[5] Yang M,Zhang L,Zhang D.Metaface:learning for sparse representation based face recognition[A].Proceedings of the 17th International Conference on Image Processing[C].Hong Kong,China:IEEE Computer Society,2010.1601-1604.
[6] Yang M,Zhang L,Feng X C,Zhang D.Sparse representation based Fisher discrimination dictionary learning for image classification[J].International Journal of Computer Vision,2014,109(3):209-232.
[7] Liu C,Wechsler H.Gabor feature based classification using the enhanced Fisher linear discriminant model for face recognition[J].IEEE Transactions on Image Processing,2002,11(4):467-476.
[8] 张文超,山世光,张洪明,陈杰,陈熙林,高文.基于局部Gabor变化直方图序列的人脸描述与识别[J].软件学报,2006,17(12):2508-2517. Zhang Wenchao,Shan Shiguang,Zhang Hongming,Chen Jie,Chen Xilin,Gao Wen.Histogram sequence of local Gabor binary pattern for face description and identification[J].Journal of Software,2006,17(12):2508-2517.(in Chinese)
[9] 李宽,殷建平,李永,刘发耀.基于Gabor系数分块统计和自适应特征选择的人脸描述与识别[J].计算机研究与发展,2012,49(4):777-784. Li Kuan,Yin Jianping,Li Yong,Liu Fayao.Local statistical analysis of Gabor coefficients and adaptive feature extraction for face description and recognition[J].Journal of Computer Research and Development,2012,49(4):777-784.(in Chinese)
[10] Yang M,Zhang L,Shiu S,Zhang D.Robust kernel representation with statistical local features for face recognition[J].IEEE Transactions on Neural Networks and Learning Systems,2013,24(6):900-912.
[11] Tan K R,Chen S C.Adaptively weighted subpattern PCA for face recognition[J].Neurocomputing,2004,64:505-511.
[12] Kumar R,Banerjee A,Vemuri B C.Volterafaces:discriminant analysis using volterra kernels[A].Proceedings of the 22nd Conference on Computer Vision and Pattern Recognition[C].Miami,USA:IEEE Computer Society,2009.150-155.
[13] Zhu P F,Zhang L,Hu Q H,Shiu S.Multi-scale patch based collaborative representation for face recognition with margin distribution optimization[A].Proceedings of the 12th European Conference on Computer Vision[C].Florence,Italy:Springer-Verlag,2012.822-835.
[14] 朱玉莲,陈松灿.特征采样和特征融合的子图像人脸识别方法[J].软件学报,2012,23(12):3209-3220. Zhu Yulian,Chen Songcan.Sub-image method based on feature sampling and feature fusion for face recognition[J].Journal of Software,2012,23(12):3209-3220.(in Chinese)
[15] Cai D,He X F,Han J W,Zhang H J.Orthogonal Laplacian faces for face recognition[J].IEEE Transactions on Image Processing,2006,15(11):3608-3614.
2016, Vol. 44 
