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Conference Paper: Linear subspace learning based on a learned discriminative dictionary for sparse coding
Title | Linear subspace learning based on a learned discriminative dictionary for sparse coding |
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Authors | |
Keywords | Discriminative dictionary learning Face recognition Linear subspace learning |
Issue Date | 2013 |
Citation | The 8th International Conference on Computer Vision Theory and Applications (VISAPP 2013), Barcelona, Spain, 21-24 February 2013. In Proceedings of 8th VISAPP, 2013, v. 1, p. 530-538 How to Cite? |
Abstract | Learning linear subspaces for high-dimensional data is an important task in pattern recognition. A modern approach for linear subspace learning decomposes every training image into a more discriminative part (MDP) and a less discriminative part (LDP) via sparse coding before learning the projection matrix. In this paper, we present a new linear subspace learning algorithm through discriminative dictionary learning. Our main contribution is a new objective function and its associated algorithm for learning an over-complete discriminative dictionary from a set of labeled training examples. We use a Fisher ratio defined over sparse coding coefficients as the objective function. Atoms from the optimized dictionary are used for subsequent image decomposition. We obtain local MDPs and LDPs by dividing images into rectangular blocks, followed by block-wise feature grouping and image decomposition. We learn a global linear projection with higher classification accuracy through the local MDPs and LDPs. Experimental results on benchmark face image databases demonstrate the effectiveness of our method. |
Description | VISAPP is part of VISIGRAPP - the 9th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications |
Persistent Identifier | http://hdl.handle.net/10722/186493 |
ISBN |
DC Field | Value | Language |
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dc.contributor.author | Gao, S | en_US |
dc.contributor.author | Yu, Y | en_US |
dc.contributor.author | Cheng, Y | en_US |
dc.date.accessioned | 2013-08-20T12:11:13Z | - |
dc.date.available | 2013-08-20T12:11:13Z | - |
dc.date.issued | 2013 | en_US |
dc.identifier.citation | The 8th International Conference on Computer Vision Theory and Applications (VISAPP 2013), Barcelona, Spain, 21-24 February 2013. In Proceedings of 8th VISAPP, 2013, v. 1, p. 530-538 | en_US |
dc.identifier.isbn | 978-989856547-1 | - |
dc.identifier.uri | http://hdl.handle.net/10722/186493 | - |
dc.description | VISAPP is part of VISIGRAPP - the 9th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications | - |
dc.description.abstract | Learning linear subspaces for high-dimensional data is an important task in pattern recognition. A modern approach for linear subspace learning decomposes every training image into a more discriminative part (MDP) and a less discriminative part (LDP) via sparse coding before learning the projection matrix. In this paper, we present a new linear subspace learning algorithm through discriminative dictionary learning. Our main contribution is a new objective function and its associated algorithm for learning an over-complete discriminative dictionary from a set of labeled training examples. We use a Fisher ratio defined over sparse coding coefficients as the objective function. Atoms from the optimized dictionary are used for subsequent image decomposition. We obtain local MDPs and LDPs by dividing images into rectangular blocks, followed by block-wise feature grouping and image decomposition. We learn a global linear projection with higher classification accuracy through the local MDPs and LDPs. Experimental results on benchmark face image databases demonstrate the effectiveness of our method. | - |
dc.language | eng | en_US |
dc.relation.ispartof | VISAPP 2013 - Proceedings of the International Conference on Computer Vision Theory and Applications | en_US |
dc.subject | Discriminative dictionary learning | - |
dc.subject | Face recognition | - |
dc.subject | Linear subspace learning | - |
dc.title | Linear subspace learning based on a learned discriminative dictionary for sparse coding | en_US |
dc.type | Conference_Paper | en_US |
dc.identifier.email | Yu, Y: yzyu@cs.hku.hk | en_US |
dc.identifier.authority | Yu, Y=rp01415 | en_US |
dc.identifier.scopus | eid_2-s2.0-84878255456 | - |
dc.identifier.hkuros | 220945 | en_US |
dc.identifier.volume | 1 | - |
dc.identifier.spage | 530 | en_US |
dc.identifier.epage | 538 | en_US |
dc.customcontrol.immutable | sml 130830 | - |