Face recognition using virtual parametric eigenspace signatures
D.B. Graham · 1997
This paper proposes a novel system for Face Recognition which utilises the Parametric Eigenspace of Murase and Nayar [8] to determine both the pose and identification of a face held within a current face database. In order that all views from profile to frontal are available for recognition a sample of views are taken from a range of angles so that, during the identification process, virtual views can be estimated from a novel view to supply ordered coordinates in the eigenvector subspace for the recognition algorithm. The method is demonstrated on a set of faces and results show that the technique is practical. The system is described in the context of a theoretical model of human face recognition which closely resembles that described in the literature. INTRODUCTION The majority of current Face Recognition (FR) systems have concentrated on the problem of recognising human faces from the frontal or near-frontal view, indeed some systems quantify their degree of tolerance from the fron...