参考文献/References:
[1] Turk M,Pentland A.Eigenfaces for recognition[J].Journal of Cognitive Neuroscience,1991,3(1):71-86.
[2]Belhumeur P N,Hespanha J P,Kriegman D J.Eigenfaces vs Fisherfaces:Recognition using class specific linear projection[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1997,19(7):711-720.
[3]杨章静,刘传才,顾兴健,等.依概率分类的保持投影及其在人脸识别中的应用[J].南京理工大学学报,2013,37(1):7-11.
Yang Zhangjing,Liu Chuancai,Gu Xingjian,et al.Probabilistic classification preserving projections and its application to face recognition[J].Journal of Nanjing University of Science and Technology,2013,37(1):7-11.
[4]He X F,Yan S,Hu Y,et al.Face recognition using Laplacianfaces[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2005,27(3):328-340.
[5]王建国,杨万扣,郑宇杰,等.一种基于ICA和模糊LDA的特征提取方法[J].模式识别与人工智能,2008(6):819-823.
Wang Jianguo,Yang Wankou,Zheng Yujie,et al.A feature extraction method based on ICA and fuzzy LDA[J].Pattern Recognition and Artificial Intelligence,2008(6):819-823.
[6]Schölkopf B,Smola A J,Muller K R.Nonlinear component analysis as a kernel eigenvalue problem[J].Neural computation,1998,10:1299-1319.
[7]Mika S,Rätsch G,Weston J,et al.Fisher discriminant analysis with kernels[J].Neural Networks for Signal Processing,1999,9:41-48.
[8]Wright J,Yang A Y,Ganesh A,et al.Robust face recognition via sparse representation[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2009,31(2):210-226.
[9]Zhang L,Yang M,Feng X.Sparse representation or collaborative representation:Which helps face recognition?[C]//Proceedings of the 2011 Interna-tional Conference on Computer Vision.Barcelona,Spain:IEEE Computer Society,2011:471-478.
[10]Yang M,Zhang L,Yang J,et al.Robust sparse coding for face recognition[C]//Proceedings of the 24th International Conference on Computer Vision and Pattern Recognition.Colorado Springs,US:IEEE Computer Society,2011,42(7):625-632.
[11]Yang M,Zhang L,Feng X C,et al.Sparse representation based Fisher discrimination dictionary learning for image classification[J].International Journal of Computer Vision,2014,109(3):209-232.
[12]Chen S,Liu J,Zhou Z.Making FLDA applicable to face recognition with one sample per person[J].Pattern Recognition,2004,37(7):1553-1555.
[13]Li Zisheng,Imai Jun-ichi,Masahide Kaneko.Robust face recognition using block-based bag of words[C]//Proceedings of the 26th International Conference on Pattern Recognition.Istanbul,Turkey:IEEE,2010:1285-1288.
[14]Zhen Cui,Wen Li,Dong Xu,et al.Fusing robust face region descriptors via multiple metric learning for face recognition in the wild[C]//Proceedings of the 26th International Conference on Computer Vision and Pattern Recognition.Portland,US:IEEE,2013:3554-3561.
[15]Hofmann T.Unsupervised learning by probabilistic latent semantic analysis[J].Machine Learning,2001,42(1):177-196.
相似文献/References:
[1]程勇,赵春霞,王欢,等.基于NSCT和SQI的光照不变量及人脸识别[J].南京理工大学学报(自然科学版),2010,(04):425.
CHENG Yong,ZHAO Chun-xia,WANG Huan,et al.Illumination Invariant and Face Recognition Based on NSCT and SQI[J].Journal of Nanjing University of Science and Technology,2010,(05):425.
[2]范燕,於东军,宋晓宁,等.镜像基函数下过渡投影子空间人脸特征抽取算法[J].南京理工大学学报(自然科学版),2012,36(06):0.
FAN Yan,YU Dong jun,SONG Xiao ning,et al.Face Feature Extraction Approach of Projective Transition Subspace Based on Basis Function of Mirror Symmetry[J].Journal of Nanjing University of Science and Technology,2012,36(05):0.
[3]杨章静,刘传才,顾兴健,等.依概率分类的保持投影及其在人脸识别中的应用[J].南京理工大学学报(自然科学版),2013,37(01):7.
Yang Zhangjing,Liu Chuancai,Gu Xingjian,et al.Probabilistic classification preserving projections and its application
to face recognition[J].Journal of Nanjing University of Science and Technology,2013,37(05):7.
[4]黄修武,郭跃飞,杨静宇.基于代数方法的图像特征抽取和识别[J].南京理工大学学报(自然科学版),1998,(01):5.
Huang Xiuwu Guo Yuefei Yang Jingyu.Image Feature Extraction and Recognition Based on Algebraic Method[J].Journal of Nanjing University of Science and Technology,1998,(05):5.
[5]张琳梅,张雪峰.曲波变换和独立分量分析的人脸识别[J].南京理工大学学报(自然科学版),2017,41(01):74.[doi:10.14177/j.cnki.32-1397n.2017.41.01.010]
Zhang Linmei,Zhang Xuefeng.Face recognition based on curvelet transform and independentcomponent analysis[J].Journal of Nanjing University of Science and Technology,2017,41(05):74.[doi:10.14177/j.cnki.32-1397n.2017.41.01.010]