Face recognition using statistical models

We describe the use of flexible models for the representation of shape and grey-level appearance of human faces. The models are controlled by a small number of parameters, which can be used to code the overall appearance of a face for image compression and classification. Shape and grey-level appearance are included in a single model. Discriminant analysis allows the isolation of variation important for classification of identity. We have performed both face recognition and face synthesis experiments and present the results in this paper.