Fan J F, Chen D S. Combining manifold learning and nonlinear regression for head pose estimation[J]. Journal of Image and Graphics, 2012, 17(8): 1002-1010. [范进富, 陈锻生. 流形学习与非线性回归结合的头部姿态估计[J]. 中国图象图形学报, 2012, 17(8): 1002-1010.]
[2]
Izenman A J. Introduction to manifold learning[J]. Wiley Interdisciplinary Reviews: Computational Statistics, 2012, 4(5): 439-446.
[3]
Seung H S, Lee D D. The manifold ways of perception[J]. Science, 2000, 290(5500): 2268-2269.
[4]
Roweis S T, Saul L K. Nonlinear dimensionality reduction by locally linear embedding[J]. Science, 2000, 290(5500): 2323-2326.
[5]
de Ridder D, Kouropteva O, Okun O, et al. Supervised locally linear embedding[C]//Artificial Neural Networks and Neural Information Processing. Berlin Heidelberg: Springer, 2003, 333-341.
[6]
He X, Cai D, Yan S, et al. Neighborhood preserving embedding[C]//Proceedings of IEEE the 10th International Conference on Computer Vision. Beijing, China: IEEE, 2005, 2:1208-1213.
[7]
Pang Y, Zhang L, Liu Z, et al. Neighborhood preserving projections (NPP): a novel linear dimension reduction method[C]//Advances in Intelligent Computing. Berlin Heidelberg: Springer, 2005: 117-125.
[8]
Wen G H, Jiang L J, Wen J. Dynamically determining neighborhood parameter for locally linear embedding[J]. Journal of Software, 2008, 19(7): 1666-1673. [文贵华, 江丽君, 文军. 邻域参数动态变化的局部线性嵌入[J]. 软件学报, 2008, 19(7): 1666-1673.]
[9]
Li B, Yang D, Lei M, et al. Adaptive locally linear embedding based on affinity propagation[J]. Journal of Optoelectronics?Laser, 2010, 21(5): 772-778. [李博, 杨丹, 雷明, 等. 基于近邻消息传递的自适应局部线性嵌入[J]. 光电子?激光, 2010, 21(5): 772-778.]
[10]
Hui K H, Xiao B H, Wang C H. Self-regulation of neighborhood parameter for locally linear embedding[J]. Pattern Recognition and Artificial Intelligence, 2010, 23(6): 842-846. [惠康华, 肖柏华, 王春恒. 基于自适应近邻参数的局部线性嵌入[J]. 模式识别与人工智能, 2010, 23(6): 842-846.]
[11]
Ge S S, Yang Y, Lee T H. Hand gesture recognition and tracking based on distributed locally linear embedding[J]. Image and Vision Computing, 2008, 26(12): 1607-1620.
[12]
Pan Y, Ge S S, Al Mamun A. Weighted locally linear embedding for dimension reduction[J]. Pattern Recognition, 2009, 42(5): 798-811.
[13]
Simard P Y, Le Cun Y A, Denker J S, et al. Transformation invariance in pattern recognition: tangent distance and propagation[J]. International Journal of Imaging Systems and Technology, 2000, 11(3): 181-197.
[14]
Yang B, Chen S. Sample-dependent graph construction with application to dimensionality reduction[J]. Neurocomputing, 2010, 74(1): 301-314.
[15]
Saxena A, Gupta A, Mukerjee A. Non-linear dimensionality reduction by locally linear isomaps[C]//Neural Information Processing. Calcutta, West Bengal, India: Springer, 2004:1038-1043.