Objectives:
In this laboratory exercise, you are given 20 face images, which are used as training samples for PCA.
You are required to produce the eigenfaces of the training samples, which are then used to form an
eigenspace for face representation and recognition based on 4 testing images (2 face images and 2 non-
face images). Through this exercise, you will learn the following:
1. representation of a face image as a high-dimensional vector;
2. generation of the principal components of a set of training images;
3. approximation of images using the principal components; and
4. face recognition using PCA.
Software Tools: MATLAB is used throughout this laboratory. You may refer to the HELP menu for the
MATLAB commands used in this laboratory.
Hi, I'm having image and video processing course this semester, and have to do all the practicals in matlab. So i'm having pretty decent knowledge in matlab and image processing and willing to explore as much as possible.
I'd like to take on this project. thanks