Face recognition from unfamiliar views: subspace methods and pose dependency

Abstract

A framework for recognising human faces from unfamiliar views is described and a simple implementation of this framework evaluated. The interaction between training view and testing view is shown to compare with observations in human face recognition experiments. The ability of the system to learn from several training views, as available in video footage, is shown to improve the overall performance of the system as is the use of multiple testing images.