Robust 3D Face Recognition from Expression Categorisation

Cook, Jamie A., Cox, Mark D., Chandran, Vinod, & Sridharan, Sridha (2007) Robust 3D Face Recognition from Expression Categorisation. In International Conference on Biometrics, September, Seoul, Korea.

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The task of Face Recognition is often cited as being complicated by the presence of lighting and expression variation. In this article a novel combination of facial expression categorisation and 3D Face Recognition is used to provide enhanced recognition performance. The use of 3D face data alleviates performance issues related to pose and illumination. Part-face decomposition is combined with a novel adaptive weighting scheme to increase robustness to expression variation. By using local features instead of a monolithic approach, this system configuration allows for expression variability to be modelled and aid in the fusion process. The system is tested on the Face Recognition Grand Challenge (FRGC) database, currently the largest available dataset of 3D faces. The sensitivity of the proposed approach is also evaluated in the presence of systematic error in the expression classification stage.

Impact and interest:

4 citations in Scopus
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3 citations in Web of Science®

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247 since deposited on 26 Nov 2007
10 in the past twelve months

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ID Code: 10913
Item Type: Conference Paper
Refereed: Yes
Keywords: face recognition, expression, gabor, part face, FRGC
DOI: 10.1007/978-3-540-74549-5_29
ISBN: 9783540745488
ISSN: 1611-3349
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Computer Vision (080104)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Adaptive Agents and Intelligent Robotics (080101)
Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Past > Institutes > Information Security Institute
Copyright Owner: Copyright 2007 Springer
Copyright Statement: This is the author-version of the work. Conference proceedings published, by Springer Verlag, will be available via SpringerLink.
Deposited On: 26 Nov 2007 00:00
Last Modified: 29 Feb 2012 13:41

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