Name
Abstract | ||
|---|---|---|
In this work we aim to study rigorously the facial age estimation in a multiethnic environment with 39 possible combination of four feature normalization methods, two simple feature fusion methods, two feature selection methods, and three face representation methods as Gabor, AAM and LBP. First, Gabor feature is extracted as facial representation for age estimation. Inspired by [3], we further fuse the global Active Appearance Model (AAM) and the local Gabor features as the representation of faces. Combining with feature selection schemes such as Least Angle Regression (LAR) and sequential selection, an advanced age estimation system is proposed on the fused features. Systematic comparative of 39 experiments demonstrate that (1) As a single facial representation, Gabor features surprisedly outperform LBP features or even AAM features. (2) With global/local feature fusion scheme, fused Gabor and AAM or fused LBP and AAM features can achieve significant improvement in age estimation over single feature representation alone. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-25449-9_26 | CCBR |
Keywords | Field | DocType |
fused feature,local feature fusion scheme,lbp feature,gabor feature,facial age estimation,feature selection scheme,feature selection method,local gabor feature,age estimation,aam feature,feature normalization method | Computer vision,Sequential selection,Feature fusion,Normalization (statistics),Feature selection,Pattern recognition,Gabor wavelet,Computer science,Local binary patterns,Active appearance model,Artificial intelligence,Least-angle regression | Conference |
Volume | ISSN | Citations |
7098 | 0302-9743 | 2 |
PageRank | References | Authors |
0.39 | 17 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Cuixian Chen | 1 | 53 | 6.38 |
| Wankou Yang | 2 | 535 | 34.68 |
| Yishi Wang | 3 | 43 | 5.50 |
| Shiguang Shan | 4 | 6322 | 283.75 |
| Karl Ricanek | 5 | 165 | 18.65 |