Title :
Feature Modelling of PCA Difference Vectors for 2D and 3D Face Recognition
Author :
McCool, Chris ; Cook, Jamie ; Chandran, Vinod ; Sridharan, Sridha
Author_Institution :
Queensland University of Technology, Australia
Abstract :
This paper examines the the effectiveness of feature modelling to conduct 2D and 3D face recognition. In particular, PCA difference vectors are modelled using Gaussian Mixture Models (GMMs) which describe Intra-Personal (IP) and Extra-Personal (EP) variations. Two classifiers, an IP and IPEP classifier, are formed using these GMMs and their performance is compared to that of the Mahalanobis cosine metric (MahCosine). The best results for the 2D and 3D face modalities are obtained with the IP and IPEP classifiers respectively. The multi-modal fusion of these two systems provided consistent performance improvement across the FRGC database v2.0.
Keywords :
Australia; Biometrics; Costs; Data mining; Databases; Discrete cosine transforms; Face recognition; Feature extraction; Laboratories; Principal component analysis;
Conference_Titel :
Video and Signal Based Surveillance, 2006. AVSS '06. IEEE International Conference on
Conference_Location :
Sydney, Australia
Print_ISBN :
0-7695-2688-8
DOI :
10.1109/AVSS.2006.50
