Using non-negative matrix factorization (NMF) for facial recognition
One major issue with this approach is that if you represent your image as a vector of pixel intensities, you have zero translation-invariance.  Two pictures that are exactly the same but shifted over 10 pixels will likely look like dissimilar vectors.  That is why people try to use other methods that handle translation, like convolutional neural networks or SIFT features.