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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Chao Wang Zhiqi Shen |
| Copyright Year | 2011 |
| Description | Author affiliation: School of Electrical & Electronics Engineering Nanyang Technological University, Singapore (Chao Wang; Zhiqi Shen) |
| Abstract | Facial expression recognition plays an important role in interactive entertainment. In this paper, LSFA (Local Sensitive Frontier Analysis) a novel feature extraction method is introduced for facial expression recognition. LSFA is designed as manifold based feature extraction method to obtain useful features from the facial expression pictures, since the facial expression scatter in high dimensional space as a point will embed in low dimensional manifold. From comparing several feature extraction methods in the experiment, it can be found that this algorithm gets better expression recognition result. |
| Starting Page | 1 |
| Ending Page | 4 |
| File Size | 210464 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781457700293 |
| e-ISBN | 9781457700316 |
| DOI | 10.1109/ICICS.2011.6173611 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-12-13 |
| Publisher Place | Singapore |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Manifolds Face recognition Feature extraction Face Algorithm design and analysis Educational institutions Machine learning Facial Expression Manifold Learning LSFA |
| Content Type | Text |
| Resource Type | Article |
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