Name
Abstract | ||
|---|---|---|
Local binary pattern on three orthogonal planes (LBP-TOP) is one of the most popular method for dynamic texture analysis and has been successfully applied to facial expression analysis. Yet an effective LBP-TOP operator highly relies on preprocessing. And, like many appearance-based approaches, this approach reserves more identity-related cues rather than expression. In this work, we propose a fully automatic approach for facial expression recognition based on points registration, localized patch extraction and LBP-TOP feature representation. The efficiency of this method is evaluated on CK+ database. Results show that the proposed method has achieved a better performance compared with existing methods. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/HSI.2015.7170694 | HSI |
Keywords | Field | DocType |
histograms,support vector machines,face,feature extraction,face recognition | Computer vision,Histogram,Facial recognition system,Three-dimensional face recognition,Pattern recognition,Computer science,Local binary patterns,Support vector machine,Feature extraction,Feature (machine learning),Facial expression,Artificial intelligence | Conference |
ISSN | Citations | PageRank |
2158-2246 | 2 | 0.37 |
References | Authors | |
19 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Y. Wang | 1 | 15 | 7.44 |
| Hui Yu | 2 | 128 | 21.50 |
| Brett Stevens | 3 | 222 | 31.38 |
| Honghai Liu | 4 | 1974 | 178.69 |