Efficient tensor based face recognition
This paper addresses the limitation of current multilinear PCA based techniques, in terms of prohibitive computational cost of testing and poor generalisation in some scenarios, when applied to large training databases. We define person-specific eigenmodes to obtain a set of projection bases, wherei...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Published: |
IEEE
2008
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| Online Access: | http://hdl.handle.net/20.500.11937/31640 |
| _version_ | 1848753438119165952 |
|---|---|
| author | Rana, Santu Liu, Wan-Quan Lazarescu, Mihai Venkatesh, Svetha |
| author2 | Not known |
| author_facet | Not known Rana, Santu Liu, Wan-Quan Lazarescu, Mihai Venkatesh, Svetha |
| author_sort | Rana, Santu |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | This paper addresses the limitation of current multilinear PCA based techniques, in terms of prohibitive computational cost of testing and poor generalisation in some scenarios, when applied to large training databases. We define person-specific eigenmodes to obtain a set of projection bases, wherein a particular basis captures variation across lightings and viewpoints for a particular person. A new recognition approach is developed utilizing these bases. The proposed approach performs on a par with the existing multilinear approaches, whilst significantly reducing the complexity order of the testing algorithm. |
| first_indexed | 2025-11-14T08:24:31Z |
| format | Conference Paper |
| id | curtin-20.500.11937-31640 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:24:31Z |
| publishDate | 2008 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-316402018-03-29T09:08:51Z Efficient tensor based face recognition Rana, Santu Liu, Wan-Quan Lazarescu, Mihai Venkatesh, Svetha Not known This paper addresses the limitation of current multilinear PCA based techniques, in terms of prohibitive computational cost of testing and poor generalisation in some scenarios, when applied to large training databases. We define person-specific eigenmodes to obtain a set of projection bases, wherein a particular basis captures variation across lightings and viewpoints for a particular person. A new recognition approach is developed utilizing these bases. The proposed approach performs on a par with the existing multilinear approaches, whilst significantly reducing the complexity order of the testing algorithm. 2008 Conference Paper http://hdl.handle.net/20.500.11937/31640 10.1109/ICPR.2008.4761706 IEEE restricted |
| spellingShingle | Rana, Santu Liu, Wan-Quan Lazarescu, Mihai Venkatesh, Svetha Efficient tensor based face recognition |
| title | Efficient tensor based face recognition |
| title_full | Efficient tensor based face recognition |
| title_fullStr | Efficient tensor based face recognition |
| title_full_unstemmed | Efficient tensor based face recognition |
| title_short | Efficient tensor based face recognition |
| title_sort | efficient tensor based face recognition |
| url | http://hdl.handle.net/20.500.11937/31640 |