Imperial College London
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ProfessorDuncanGillies

Faculty of Engineering, Department of Computing

Emeritus Professor
 
 
 
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Contact

 

+44 (0)20 7594 8317d.gillies Website

 
 
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Location

 

373Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Minoi:2012:10.1109/ICSSBE.2012.6396626,
author = {Minoi, JL and Thomaz, CE and Gillies, DF},
doi = {10.1109/ICSSBE.2012.6396626},
journal = {ICSSBE 2012 - Proceedings, 2012 International Conference on Statistics in Science, Business and Engineering: "Empowering Decision Making with Statistical Sciences"},
pages = {552--557},
title = {Tensor-based multivariate statistical discriminant methods for face applications},
url = {http://dx.doi.org/10.1109/ICSSBE.2012.6396626},
year = {2012}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - This paper describes the use of tensor-based multivariate statistical discriminant methods in three-dimensional face applications for synthesis and modelling of face shapes and for recognition. The methods could recognise faces and facial expressions, synthesize new face shapes and generate facial expressions based on the the most discriminant vectors calculated in the training sets that contain classes of face shapes and facial expressions. The strength of the introduced methods is that varying degrees of face shapes can be generated given that only a small number of 3D face shapes are available in the dataset. This framework also has the ability to characterise face variations across subjects and facial expressions. Recognition experiment was conducted using 3D face database created by the State University of New York (SUNY), Binghamton. The results have shown higher recognition rates for face and facial expression compared to the more popular eigenface techniques. The outcome of the synthesis of face shapes and facial expressions will also be presented here. © 2012 IEEE.
AU  - Minoi,JL
AU  - Thomaz,CE
AU  - Gillies,DF
DO  - 10.1109/ICSSBE.2012.6396626
EP  - 557
PY  - 2012///
SP  - 552
TI  - Tensor-based multivariate statistical discriminant methods for face applications
T2  - ICSSBE 2012 - Proceedings, 2012 International Conference on Statistics in Science, Business and Engineering: "Empowering Decision Making with Statistical Sciences"
UR  - http://dx.doi.org/10.1109/ICSSBE.2012.6396626
ER  -
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