Mahalanobis distance-based semi-supervised discriminant analysis for face recognition

[1] Turk M A,Pentland A P.Face recognition using eigenfaces //Proc 91 IEEE Comput Soc Conf Comput Vision Pattern Recognit.Piscataway,NJ:IEEE,1991:586-591 [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] He Xiaofei,Niyogi P.Locality preserving projections //Proceedings of the Conference on Advances in Neural Information Processing Systems.Cambridge:MIT Press,2003:153-160 [4] Yan Shuicheng,Xu Dong,Zhang Benyu,et al.Graph embedding and extension:a general framework for dimensionality reduction[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2007,29(1):40-51 [5] Xing E P,Ng A Y,Jordan M I,et al.Distance metric learning,with application to clustering with side-information[M].Cambridge:MIT Press,2003:505-512 [6] 何晓群.多元统计分析[M].北京:中国人民大学出版社,2004:6-76 He Xiaoqun.Multivariate statistical analysis[M].Beijing:Renmin University of China Press,2004:6-76(in Chinese) [7] 黄飞,周军,卢晓东.基于马氏距离的一维距离像识别算法仿真[J].计算机仿真,2010,27(3):31-34 Huang Fei,Zhou Jun,Lu Xiaodong.The simulation of one-dimensional range profile recognition based on mahalanobis distance[J].Computer Simulation,2010,27(3):31-34(in Chinese) [8] Aouada D,Baryshnikov Y,Krim H.Mahalanobis-based adaptive nonlinear dimension reduction //Proceedings-International Conference on Pattern Recognition.Piscataway,NJ:IEEE,2010:742-745 [9] Cai Deng,He Xiaofei,Han Jiawei.Semi-supervised discriminant analysis //Proceedings of the IEEE International Conference on Computer Vision.Piscataway,NJ:IEEE,2007:1-7 [10] Remus S,Tomasi C.Semi-supervised fisher linear discriminant (SFLD) //IEEE International Conference on Acoustics,Speech and Signal Processing.Piscataway,NJ:IEEE,2010:1862-1865