二维PCA.doc

二维PCA-人脸识别--源程序(matlab)
%更多给我邮件 我的空间有邮件地址
function pca (path, trainList, subDim)
%
% PROTOTYPE
% function pca (path, trainList, subDim)
%
% USAGE EXAMPLE(S)
% pca ('C:/FERET_Normalised/', trainList500Imgs, 200);
%
% GENERAL DESCRIPTION
% Implements the standard Turk-Pentland Eigenfaces method. As a final
% result, this function saves pcaProj matrix to the disk with all images
% projected onto the subDim-dimensional subspace found by PCA.
%
% REFERENCES
% M. Turk, A. Pentland, Eigenfaces for Recognition, Journal of Cognitive
% Neurosicence, Vol. 3, No. 1, 1991, pp. 71-86
%
% . Turk, . Pentland, Face Recognition Using Eigenfaces, Proceedings
% of the IEEE Conference on Computer Vision and Pattern Recognition,
% 3-6 June 1991, Maui, Hawaii, USA, pp. 586-591
%
%
% INPUTS:
% path - full path to the normalised images from FERET database
% trainList - list of images to be used for training. names should be
% without extension and .pgm will be added automatically
% subDim - Numer of dimensions to be retained (the desired subspace
% dimensionality). if this argument is ommited, maximum
% non-zero dimensions will be retained, . (number of training images) - 1
%
% OUTPUTS:
% Function will generate and save to the disk the following outputs:
% DATA - matrix where