Low Dimensional Surface Parameterisation with Applications in Biometrics

Authors:
Wei Quan;Bogdan J. Matuszewski;Lik-Kwan Shark;Djamel Ait-Boudaoud
Affiliations:
University of Central Lancashire, Preston PR1 2HE, United Kingdom;University of Central Lancashire, Preston PR1 2HE, United Kingdom;University of Central Lancashire, Preston PR1 2HE, United Kingdom;University of Central Lancashire, Preston PR1 2HE, United Kingdom
Venue:
MEDIVIS '07 Proceedings of the International Conference on Medical Information Visualisation - BioMedical Visualisation
Year:
2007

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Abstract

This paper describes initial results from a novel low dimensional surface parameterisation approach based on a modified Iterative Closest Point (ICP) registration process which uses vertex based Principal Component Analysis (PCA) to incorporate a deformable element into registration process. Using this method a 3-D surface is represented by a shape space vector of much smaller dimensionality than the dimensionality of the original data space vector. The proposed method is tested on both simulated 3-D faces with different facial expressions and real face data. It is shown that the proposed surface representation can be potentially used as feature space for a facial expression recognition system.