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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Inoue, K. Kuroki, Y. |
| Copyright Year | 2011 |
| Description | Author affiliation: Kurume National College of Technology, 1-1-1, Komorino, Kurume-shi, Fukuoka 830-8555 Japan (Inoue, K.; Kuroki, Y.) |
| Abstract | Sparse representation receives a lot of attention as a representation method of signals in recent years. The sparse representation-based classification (SRC) applies sparse representation to face recognition. Camera parameters and/or illumination change may occur in real situations of face recognition. This study aims to propose a illumination robust SRC. The proposed method modifies the bases which are added to training bases derived from the training data set to detect noise contained in the recognized facial image. In the case where a few training data set is prepared, this method succeeds to obtain the higher recognition rate than the conventional SRC. |
| Starting Page | 1 |
| Ending Page | 4 |
| File Size | 647051 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781457713217 |
| e-ISBN | 9781457713224 |
| e-ISBN | 9781457713200 |
| DOI | 10.1109/VCIP.2011.6115969 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-11-06 |
| Publisher Place | Taiwan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Training Face recognition Training data Lighting Minimization Sparse matrices Face |
| Content Type | Text |
| Resource Type | Article |
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