In comparison, the basic principle of Fisherfaces is that instead of calculating a special eigenvector and eigenvalue for each image in the training set, it only calculates one special eigenvector and eigenvalue for each person. So in the preceding example that has 5 people with 20 faces for each person, the Eigenfaces algorithm would use 100 eigenfaces and eigenvalues whereas the Fisherfaces algorithm would use just 5 fisherfaces and eigenvalues.