[1]HUANG W L, YIN H J. On nonlinear dimensionality reduction for face recognition [J]. Image and Vision Computing, 2012, 30(4): 355-366.[2]胡洁.高维数据特征降维研究综述[J].计算机应用研究,2008,25(9):2601-2606.[3]HOU C P, ZHANG C S, WU Y, et al. Stable local dimensionality reduction approaches [J]. Pattern Recognition, 2009, 42(9): 2054-2066.[4]TENENBAUM J B, de SILVA V, LANGFORD J C. A global geometric framework for nonlinear dimensionality reduction [J]. Science, 2000, 290(5500): 2319-2323.[5]ROWEIS S T, SAUL K L. Nonlinear dimensionality reduction by locally linear embedding [J]. Science, 2000, 290(5500): 2323-2326.[6]BELKIN M, NIYOGI P. Laplacian eigenmaps for dimensionality re-duction and data representation [J]. Neural Computing, 2003, 15(6): 1373-1396.[7]WU Y M, CHAN K L. An extended Isomap algorithm for learning multi-class manifold [C]// Proceedings of the 2004 International Conference on Machine Learning and Cybernetics. Piscataway: IEEE Press, 2004: 3429-3433. [8]GENG X, ZHAN D C, ZHOU Z H. Supervised nonlinear dimen-sionality reduction for visualization and classification [J]. IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics, 2005, 35(6): 1098-1107.[9]YANG M H. Extended Isomap for pattern classification [C]// Proceedings of the Eighteenth National Conference on Artificial Intelligence. Menlo Park: American Association for Artificial Intelligence, 2002: 224-229.[10]CHOI H, CHOI S. Robust kernel Isomap [J]. Pattern Recognition, 2007, 40(3): 853-862.[11]邵超,黄厚宽,赵连伟.一种更具拓扑稳定性的Isomap算法[J].软件学报,2007,18(4):869-877.[12]WANG L W, ZHANG Y, FENG J F. On the Euclidean distance of images [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005, 27(8): 1334-1339.[13]郝建东,张伟伟.基于核的图像欧氏距离人脸识别[J].计算机工程与设计,2011,32(11):3844-3847. |