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PCA

Dataset : jaffe

In this project, you will compute a PCA from a set of images of faces, each of size 128 * 128 in RGB format. The database provides facial images of 30 different people. For simplicity, convert the images into gray scale and resize them into 64 * 64.

Attention that, eigenfaces are sets of eigenvectors which can be used to work with face recognition applications. Each eigenface, as we'll see in a bit, appears as an array vector of pixel intensities.

We can use PCA to determine which eigenfaces contribute the largest amount of variance in our data, and to eliminate those that don't contribute much. This process lets us determine how many dimensions are necessary to recognize a face as 'familiar'.

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Principal component analysis (PCA)

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