Name
Abstract | ||
|---|---|---|
It has been noticed that the performance of multi-ethnic facial expression recognition is affected by other-race effect significantly. Though this phenomenon has been noticed by psychologists and computer vision researchers for decades, the mechanism of other-race effect is still unknown and few work has been done to compensate or remove this effect. This work proposes an ICA-based method to eliminate the other-race effect in automatic 3D facial expression recognition. Firstly, the depth features are extracted from 3D local facial patches, and independent component analysis is applied to project the features into a subspace in which the projected features are mutually independent. The ethnic-related features and expression-related features are supposed to be separated in ICA subspace. Hence, ethnic-sensitive features are then determined by an entropy-based feature selection method and discarded to depress their influence on facial expression recognition. The proposed method is evaluated on benchmark BU-3DFE database, and the experimental results reveal that the influence caused by other-race effect can be suppressed effectively with the proposed method. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.3934/mfc.2019004 | MATHEMATICAL FOUNDATIONS OF COMPUTING |
Keywords | DocType | Volume |
Facial expression recognition, other-race effect, 3D facial feature extraction, independent component analysis, feature selection | Journal | 2 |
Issue | Citations | PageRank |
1 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mingliang Xue | 1 | 0 | 0.34 |
| Duan Xiaodong | 2 | 85 | 16.18 |
| Wanquan Liu | 3 | 629 | 81.29 |