Name
Title | ||
|---|---|---|
Weighted similarity and distance metric learning for unconstrained face verification with 3D frontalisation |
Abstract | ||
|---|---|---|
In this study, the authors focus on the challenging problem of verifying faces captured under unconstrained conditions. Unconstrained face images often vary largely in poses, illuminations, expressions, occlusions, and ages. To address these challenges, they combine face frontalisation method with metric learning. To deal with the variations of poses, they apply an improved 3D face frontalisation method to generate the frontal view of the face images. Recent studies observed that bilinear similarity and Mahalanobis distance have a promising performance on measuring the similarity of two images. Based on these studies, they propose a weighted similarity and distance metric learning method which balances the role of bilinear similarity and Mahalanobis distance to better measure the similarity of an image pair. All the experiments are conducted based on the labelled faces in the wild database, and the experimental results show the effectiveness of their method. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1049/iet-ipr.2018.6327 | IET Image Processing |
Keywords | Field | DocType |
face recognition,learning (artificial intelligence) | Face verification,Computer vision,Expression (mathematics),Pattern recognition,Metric (mathematics),Mahalanobis distance,Artificial intelligence,Mathematics,Bilinear interpolation | Journal |
Volume | Issue | ISSN |
13 | 2 | 1751-9659 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xin Xu | 1 | 162 | 40.08 |
| Jiuzhen Liang | 2 | 14 | 3.75 |
| Chen Chen | 3 | 145 | 21.68 |
| Zhenjie Hou | 4 | 0 | 0.34 |