2D-3D Face Recognition Based on PCA and Feature Modelling
Chandran, Vinod, McCool, Christopher, & Sridharan, Sridha (2006) 2D-3D Face Recognition Based on PCA and Feature Modelling. In Senac, C & Ferrane, I (Eds.) Proceedings of the Second International Workshop on MultiModal User Authentication, University of California, Toulouse, France, pp. 1-8.
Hybrid face recognition, using image (2D) and structural (3D) information, has explored the fusion of Nearest Neighbour classifiers. This paper examines the effectiveness of feature modelling for each individual modality, 2D and 3D. Furthermore, it is demonstrated that the fusion of feature modelling techniques for the 2D and 3D modalities yields performance improvements over the individual classifiers. By fusing the feature modelling classifiers for each modality with equal weights the average Equal Error Rate improves from 12.60% for the 2D classifier and 12.10% for the 3D classifier to 7.38% for the Hybrid 2D+3D clasiffier.
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|Item Type:||Conference Paper|
|Keywords:||Image Processing, Multi-Modal, Pattern Recognition, Face Recognition|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Image Processing (080106)|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering|
Past > Institutes > Information Security Institute
Past > Schools > School of Engineering Systems
|Deposited On:||18 Jun 2009 00:59|
|Last Modified:||29 Feb 2012 23:22|
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