PCA和FLD两种不同方法实现人脸识别

'Fisherface' Face Recognition System Written by: Amir Hossein Omidvarnia Email: aomidvar@ece.ut.ac.ir This package implements a well-known FLD-based face recognition method, which is called 'Fisherface' [1]. All functions are easy to use, as they are heavy commented. Furtheremore, a sample script is included to showe their usage. In general, you should follow this order: 1. Select training and test database paths. 2. Select path of the test image. 3. Run 'CreateDatabase' function to create 2D matrix of all training images. 4. Run 'FisherfaceCore' function to produce basis's of facespace. 5. Run 'Recognition' function to get the name of equivalent image in training database. For your convenience, I have prepared sample training and test databases, which are parts of 'face94' Essex face database [2]. You just need to copy the above functions, along with the training and test databases into a specified path (for example 'work' path of your MATLAB root). Then follow dialog boxes, which will appear upon running 'example.m'. I would like to cite persons below, as their materials were very helpful in preparing this package: 1. Hongcheng Wang,Beckman Institute, UIUC because of his useful presentation: "Facial Recognition as a Pattern Recognition Problem" 2. Alan Brooks (in collaboration with Li Gao), Final Project Report submitted on June 9, 2004 for ECE 432 Computer Vision with Professor Ying Wu Enjoy it! References: [1] P. N. Belhumeur, J. Hespanha, and D. J. Kriegman. Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection. In ECCV (1), pages 45--58, 1996. [2] Available at: http://cswww.essex.ac.uk/mv/allfaces/faces94.zip