Feature selection method based on sparse representation classification for face recognition
Compressed sensing is a signal processing technique. The entity signal can be efficiently reconstructed if the sparse representation is determined. The sparse representations of all the test images are determined with respect to the training set by computing the l1-minimization. However, sparse rep...
| Main Authors: | , |
|---|---|
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2014
|
| Subjects: | |
| Online Access: | http://eprints.sunway.edu.my/255/ http://eprints.sunway.edu.my/255/1/DCIS_Ching%20Sue%20Inn.%20Feature%20selection%20method.pdf |
| _version_ | 1848801783943528448 |
|---|---|
| author | Boon, Yinn Xi * Ch'ng, Sue Inn * |
| author_facet | Boon, Yinn Xi * Ch'ng, Sue Inn * |
| author_sort | Boon, Yinn Xi * |
| building | SU Institutional Repository |
| collection | Online Access |
| description | Compressed sensing is a signal processing technique.
The entity signal can be efficiently reconstructed if the sparse representation is determined. The sparse representations of all the test images are determined with respect to the training set by computing the l1-minimization. However, sparse representation which involves high dimensional feature vector is computationally expensive. Thus, discriminative features that could perform accurately for the face recognition system under visual variations, such as illumination, expression and occlusion have to be selected carefully. In this paper, feature selection method in the application of face recognition based on sparse representation classifier (SRC) is proposed. The proposed technique first divides the images of a few subjects into chunks. Then, it selects the feature subsets based on distance based measurement, the residual, and recognition performance, the accuracy. Extensive experiments with visual variations are carried out by using ORL, AR and Yale databases. |
| first_indexed | 2025-11-14T21:12:57Z |
| format | Conference or Workshop Item |
| id | sunway-255 |
| institution | Sunway University |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T21:12:57Z |
| publishDate | 2014 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | sunway-2552019-04-25T06:02:37Z http://eprints.sunway.edu.my/255/ Feature selection method based on sparse representation classification for face recognition Boon, Yinn Xi * Ch'ng, Sue Inn * QA75 Electronic computers. Computer science QA76 Computer software Compressed sensing is a signal processing technique. The entity signal can be efficiently reconstructed if the sparse representation is determined. The sparse representations of all the test images are determined with respect to the training set by computing the l1-minimization. However, sparse representation which involves high dimensional feature vector is computationally expensive. Thus, discriminative features that could perform accurately for the face recognition system under visual variations, such as illumination, expression and occlusion have to be selected carefully. In this paper, feature selection method in the application of face recognition based on sparse representation classifier (SRC) is proposed. The proposed technique first divides the images of a few subjects into chunks. Then, it selects the feature subsets based on distance based measurement, the residual, and recognition performance, the accuracy. Extensive experiments with visual variations are carried out by using ORL, AR and Yale databases. 2014 Conference or Workshop Item PeerReviewed text en http://eprints.sunway.edu.my/255/1/DCIS_Ching%20Sue%20Inn.%20Feature%20selection%20method.pdf Boon, Yinn Xi * and Ch'ng, Sue Inn * (2014) Feature selection method based on sparse representation classification for face recognition. In: International Conference Image Processing, Computers and Industrial Engineering (ICICIE '2014), 15 -16 Jan 2014, Kuala Lumpur. (Submitted) http://iieng.org/siteadmin/upload/3875E0114522.pdf |
| spellingShingle | QA75 Electronic computers. Computer science QA76 Computer software Boon, Yinn Xi * Ch'ng, Sue Inn * Feature selection method based on sparse representation classification for face recognition |
| title | Feature selection method based on sparse representation classification for face recognition |
| title_full | Feature selection method based on sparse representation classification for face recognition |
| title_fullStr | Feature selection method based on sparse representation classification for face recognition |
| title_full_unstemmed | Feature selection method based on sparse representation classification for face recognition |
| title_short | Feature selection method based on sparse representation classification for face recognition |
| title_sort | feature selection method based on sparse representation classification for face recognition |
| topic | QA75 Electronic computers. Computer science QA76 Computer software |
| url | http://eprints.sunway.edu.my/255/ http://eprints.sunway.edu.my/255/ http://eprints.sunway.edu.my/255/1/DCIS_Ching%20Sue%20Inn.%20Feature%20selection%20method.pdf |