Name
Abstract | ||
|---|---|---|
This paper describes a hierarchical method for image-based age estimation that combines age group classification and age value estimation. The proposed method uses a coarse-to-fine strategy with different appearance features to describe facial shape and texture. Considering the damage to continuity between neighboring groups caused by fixed divisions during age group classification, a dynamic grouping technique is employed to allow non-fixed groups. Based on the given group, an ordinal hyperplane ranking (OHRank) model is employed to transform age estimation into a series of binary enquiry problems that can take advantage of the intrinsic correlation and ordinal information of age. A set of experiments on FG-NET are presented and the results demonstrate the validity of our solution. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.3837/tiis.2014.07.016 | KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS |
Keywords | Field | DocType |
Age Estimation,hierarchical model,weighted k-NN,dynamic grouping,OHRank | Pattern recognition,Ranking,Ordinal number,Computer science,Correlation,Artificial intelligence,Hyperplane,Hierarchical database model,Binary number | Journal |
Volume | Issue | ISSN |
8 | 7 | 1976-7277 |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Li Zhang | 1 | 93 | 13.90 |
| Xianmei Wang | 2 | 3 | 3.09 |
| Yuyu Liang | 3 | 3 | 1.40 |