Tensor-based Multivariate Statistical Discriminant Methods for Face Applications
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 e...
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| Format: | Article |
| Language: | English |
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IEEE
2012
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| Online Access: | http://ir.unimas.my/id/eprint/16600/ http://ir.unimas.my/id/eprint/16600/1/Tensor-based%20Multivariate%20Statistical%20Discriminant%28abstract%29.pdf |
| _version_ | 1848838099107315712 |
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| author | Jacey-Lynn, Minoi Thomaz, Carlos E. Gillies, Duncan Fyfe |
| author_facet | Jacey-Lynn, Minoi Thomaz, Carlos E. Gillies, Duncan Fyfe |
| author_sort | Jacey-Lynn, Minoi |
| building | UNIMAS Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-15T06:50:10Z |
| format | Article |
| id | unimas-16600 |
| institution | Universiti Malaysia Sarawak |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T06:50:10Z |
| publishDate | 2012 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | unimas-166002017-06-12T04:16:43Z http://ir.unimas.my/id/eprint/16600/ Tensor-based Multivariate Statistical Discriminant Methods for Face Applications Jacey-Lynn, Minoi Thomaz, Carlos E. Gillies, Duncan Fyfe T Technology (General) 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. IEEE 2012 Article PeerReviewed text en http://ir.unimas.my/id/eprint/16600/1/Tensor-based%20Multivariate%20Statistical%20Discriminant%28abstract%29.pdf Jacey-Lynn, Minoi and Thomaz, Carlos E. and Gillies, Duncan Fyfe (2012) Tensor-based Multivariate Statistical Discriminant Methods for Face Applications. International Conference on Statistics in Science, Business, and Engineering (ICSSBE), 2012. ISSN ISBN: 978-1-4673-1582-1 http://ieeexplore.ieee.org/document/6396626/ 10.1109/ICSSBE.2012.6396626 |
| spellingShingle | T Technology (General) Jacey-Lynn, Minoi Thomaz, Carlos E. Gillies, Duncan Fyfe Tensor-based Multivariate Statistical Discriminant Methods for Face Applications |
| title | Tensor-based Multivariate Statistical Discriminant Methods for Face Applications |
| title_full | Tensor-based Multivariate Statistical Discriminant Methods for Face Applications |
| title_fullStr | Tensor-based Multivariate Statistical Discriminant Methods for Face Applications |
| title_full_unstemmed | Tensor-based Multivariate Statistical Discriminant Methods for Face Applications |
| title_short | Tensor-based Multivariate Statistical Discriminant Methods for Face Applications |
| title_sort | tensor-based multivariate statistical discriminant methods for face applications |
| topic | T Technology (General) |
| url | http://ir.unimas.my/id/eprint/16600/ http://ir.unimas.my/id/eprint/16600/ http://ir.unimas.my/id/eprint/16600/ http://ir.unimas.my/id/eprint/16600/1/Tensor-based%20Multivariate%20Statistical%20Discriminant%28abstract%29.pdf |