Face Recognition Introduction A facial recognition system is

Face Recognition Introduction A facial recognition system is a computer application for automatically identifying or verifying a person from a digital image or a video frame from a video source. One of the ways to do this is by comparing selected facial features from the image and a facial database. Flow of face recognition Face detection using eigenfaces Step 1 : Obtain face images I 1, I 2, …, IM (training faces) IMPORTANT : the faces images must be centered and of the same size It is typically used in security systems and can be compared to other biometrics such as fingerprint or eye iris recognition systems. . Step 4 : Subtract the mean face Face recognition using eigenfaces Step 5 : Compute the covariance matrix C �� Step 6 : Compute the eigenvectors ui of���� Step 7 : Keep only K eigenvectors ( corresponding to the K largest eigenvalues) Problems - Scale (performance decreases quickly with changes to the head size) * multiscale eigenspaces * scale input image to multiple sizes) - Orientation (perfomance decreases but not as fast as with scale changes) * plane rotations can be handled * out-of-plane rotations more difficult to handle - Background (deemphasize the outside of the face, e. g. , by multiplying the input image by a 2 D Gaussian window centered on the face) - Lighting conditions (performance degrades with light changes)