Tensor Based Robust Color Face Recognition
In this paper we address the robust face recognition problem for color faces with large variations in pose, illumination and facial expression. A novel algorithm is proposed, namely the Multilinear Color Tensor Discriminant (MCTD) model. This approach utilizes tensor representation to preserve image...
| Main Authors: | , , , |
|---|---|
| Other Authors: | |
| Format: | Conference Paper |
| Published: |
Institute of Electrical and Electronics Engineers (IEEE)
2012
|
| Online Access: | http://f4k.dieei.unict.it/proceedings/ICPR2012/media/files/0681.pdf http://hdl.handle.net/20.500.11937/31374 |
| _version_ | 1848753362215895040 |
|---|---|
| author | Li, Billy Liu, Wan-Quan An, Senjian Krishna, Aneesh |
| author2 | Eklundh, J-O. |
| author_facet | Eklundh, J-O. Li, Billy Liu, Wan-Quan An, Senjian Krishna, Aneesh |
| author_sort | Li, Billy |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | In this paper we address the robust face recognition problem for color faces with large variations in pose, illumination and facial expression. A novel algorithm is proposed, namely the Multilinear Color Tensor Discriminant (MCTD) model. This approach utilizes tensor representation to preserve image structure, as well as enhance discriminate capability via color space transformation. On the other hand, it uses the multilinear analysis technique to handle variations in pose, illumination and expressions and improve the performance via minimizing the least square of reconstruction error in the tensor framework. Extensive experiments conducted on the CMU-PIE and CurtinFaces databases demonstrate the effectiveness of the proposed approach. |
| first_indexed | 2025-11-14T08:23:18Z |
| format | Conference Paper |
| id | curtin-20.500.11937-31374 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:23:18Z |
| publishDate | 2012 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-313742023-02-07T08:01:19Z Tensor Based Robust Color Face Recognition Li, Billy Liu, Wan-Quan An, Senjian Krishna, Aneesh Eklundh, J-O. Ohta, Y. Tanimoto, S. In this paper we address the robust face recognition problem for color faces with large variations in pose, illumination and facial expression. A novel algorithm is proposed, namely the Multilinear Color Tensor Discriminant (MCTD) model. This approach utilizes tensor representation to preserve image structure, as well as enhance discriminate capability via color space transformation. On the other hand, it uses the multilinear analysis technique to handle variations in pose, illumination and expressions and improve the performance via minimizing the least square of reconstruction error in the tensor framework. Extensive experiments conducted on the CMU-PIE and CurtinFaces databases demonstrate the effectiveness of the proposed approach. 2012 Conference Paper http://hdl.handle.net/20.500.11937/31374 http://f4k.dieei.unict.it/proceedings/ICPR2012/media/files/0681.pdf Institute of Electrical and Electronics Engineers (IEEE) restricted |
| spellingShingle | Li, Billy Liu, Wan-Quan An, Senjian Krishna, Aneesh Tensor Based Robust Color Face Recognition |
| title | Tensor Based Robust Color Face Recognition |
| title_full | Tensor Based Robust Color Face Recognition |
| title_fullStr | Tensor Based Robust Color Face Recognition |
| title_full_unstemmed | Tensor Based Robust Color Face Recognition |
| title_short | Tensor Based Robust Color Face Recognition |
| title_sort | tensor based robust color face recognition |
| url | http://f4k.dieei.unict.it/proceedings/ICPR2012/media/files/0681.pdf http://hdl.handle.net/20.500.11937/31374 |