Name
Abstract | ||
|---|---|---|
Race identification is an essential ability for human eyes. Race classification by machine based on face image can be used in some practical application fields. Employing holistic face analysis, local feature extraction and 3D model, many race classification methods have been introduced. In this paper, we propose a novel fusion feature based on periocular region features for classifying East Asian from Caucasian. With the periocular region landmarks, we extract five local textures or geometrical features in some interesting regions which contain available discriminating race information. And then, these er effective features are fused into a remarkable feature by Adaboost training. On the composed OFD-FERET face database, our method gets perfect performance on average accuracy rate. Meanwhile, we do a plenty of additional experiments to discuss the effect on the performance caused by gender, landmark detection, glasses and image size. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1142/S0218001417500264 | INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE |
Keywords | Field | DocType |
Race classiffication, feature fusion, periocular feature, STASM, LBP | Computer vision,Feature fusion,AdaBoost,Pattern recognition,Fusion,Feature extraction,Artificial intelligence,Feature based,Landmark,Periocular Region,Mathematics,Face analysis | Journal |
Volume | Issue | ISSN |
31 | 8 | 0218-0014 |
Citations | PageRank | References |
0 | 0.34 | 10 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hengxin Chen | 1 | 1 | 0.68 |
| Mingqi Gao | 2 | 5 | 1.43 |
| Karl Ricanek | 3 | 165 | 18.65 |
| Peter Xu | 4 | 3 | 2.53 |
| Bin Fang | 5 | 3 | 4.43 |