Face recognition using perspective invariant features

Although the analytic methods based on front view facial images seem to be the best candidate for a practical facial recognition system, the existing attempts to employ these methods are not very successful. A major obstacle is the fact that these attempts do not consider perspective variations. The present paper describes an approach which makes full use of the invariant properties of a number of interfeature point distances. Our method, which considers both rotation invariance and feature normalization, achieves a very good retrieval rate when searching for an individual for whom the database contains pictures taken in different postures.