Name
Title | ||
|---|---|---|
Recognizing facial action units using independent component analysis and support vector machine |
Abstract | ||
|---|---|---|
Facial expression provides a crucial behavioral measure for studies of human emotion, cognitive processes, and social interaction. In this paper, we focus on recognizing facial action units (AUs), which represent the subtle change of facial expressions. We adopt ICA (independent component analysis) as the feature extraction and representation method and SVM (support vector machine) as the pattern classifier. By comparing with three existing systems, such as Tian, Donato, and Bazzo, our proposed system can achieve the highest recognition rates. Furthermore, the proposed system is fast since it takes only 1.8ms for classifying a test image. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1016/j.patcog.2006.03.017 | Pattern Recognition |
Keywords | Field | DocType |
Facial expression recognition,Action unit,Independent component analysis,Support vector machine | Tian,Artificial intelligence,Classifier (linguistics),Cognition,Standard test image,Pattern recognition,Support vector machine,Speech recognition,Feature extraction,Facial expression,Independent component analysis,Mathematics,Machine learning | Journal |
Volume | Issue | ISSN |
39 | 9 | 0031-3203 |
Citations | PageRank | References |
17 | 0.82 | 5 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chao-fa Chuang | 1 | 218 | 10.82 |
| Frank Y. Shih | 2 | 1103 | 89.56 |