Introduction - If you have any usage issues, please Google them yourself
Using a small sample of face image database to create the training sample data in the database ar_test.mat and sample data will produce the database file.Mat using FDDL program to test it, classification in the program finally to the effect of the short distance test feature extraction using SVD decomposition, and extracted from each image in the first 3 columns the feature vector (the first three principal components), a total of 3*200 feature vector, simple classification test results constitute a training sample column elements finally in 90 , discrimination is good, can be applied to other classification experiment. Later, the first principal component, found that the recognition rate is up to 100 the first 33, but less than 90 , explain how do?