breggularizeea
所属分类：模式识别(视觉/语音等)
开发工具：Visual C++
文件大小：3KB
下载次数：2
上传日期：2012-07-20 08:43:29
上 传 者：
segregatess
说明： 一种基于正则化转置的LDA matlab源代代码，能应用在人脸识别中，详细说明见readme
(A transpose on behalf of the LDA matlab source code based on regularization, can be applied in face recognition, a detailed description see the readme)
文件列表:
breggularizeea\F_JDLDAPro.m (4990, 2004-11-02)
breggularizeea (0, 2012-03-18)
*********************************************************************************
* Matlab source codes for the regularized linear discriminant analysis (R-LDA) *
* Author: Lu Juwei *
* Bell Canada Multimedia Lab, Dept. of ECE, U. of Toronto *
* Released in 01 November 2004 *
*********************************************************************************
The matlab functions implement the methods presented in the paper [DF_LDA_TNN.pdf]
Juwei Lu, K.N. Plataniotis, and A.N. Venetsanopoulos, "Face Recognition
Using LDA Based Algorithms", IEEE Transactions on Neural Networks, Vol. 14,
No. 1, Page: 195-200, January 2003.
and the paper [R_LDA_PRL.pdf] (An extension to the above TNN paper)
Juwei Lu, K.N. Plataniotis, A.N. Venetsanopoulos, “Regularization Studies
of Linear Discriminant Analysis in Small Sample Size Scenarios with
Application to Face Recognition”, Pattern Recognition Letter, vol. 26, issue 2,
pp. 181-191, 2005.
[Usages:]
1. To find the KDDA based feature representation with RBF kernel,
1.1. use function [DFLD_Trans]=F_JDLDAPro() to find the regularized LDA subspace.
1.2. given a sample, x, its projection (y) to the above subspace can be obtained
by y=DFLD_Trans*x.
[Note:]
The regularization parameter $eta$ in the function F_JDLDAPro() has an influence on
the classification performance. Try different values of $eta$ to find the best one.
[Restrictions:]
In all documents and papers that report on research that uses the matlab codes, the
researcher(s) must reference the following two papers:
[1] Juwei Lu, K.N. Plataniotis, and A.N. Venetsanopoulos, "Face Recognition
Using LDA Based Algorithms", IEEE Transactions on Neural Networks, Vol. 14,
No. 1, Page: 195-200, January 2003.
[2] Juwei Lu, K.N. Plataniotis, A.N. Venetsanopoulos, “Regularization Studies
of Linear Discriminant Analysis in Small Sample Size Scenarios with
Application to Face Recognition”, Pattern Recognition Letter, vol. 26, issue 2,
pp. 181-191, 2005.
Any comments and questions can be sent to juwei@dsp.utoronto.ca.
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