Recognising Trajectories of Facial Identities Using Kernel Discriminant Analysis

Y Li, S Gong and H Liddell

We present a comprehensive approach to address three challenging problems in face recognition: modelling faces across multi-views, extracting the non-linear discriminant features, and recognising faces dynamically in a spatio-temporal context. A multi-view dynamic face model is designed to extract the shape-and-pose-free facial texture patterns. Kernel Discriminant Analysis, which employs the kernel technique to perform Linear Discriminant Analysis in a high-dimensional feature space, is developed to extract the significant non-linear features which maximise the between-class variance and minimise the within-class variance. Finally, an identity surface based face recognition is performed dynamically from video input by matching object and model trajectories.

PDF version

Home Contents Author index Keyword index

Valid CSS! Valid HTML 4.01!

This document produced for BMVC 2001