Name
Title | ||
|---|---|---|
Face Recognition and Micro-expression Recognition Based on Discriminant Tensor Subspace Analysis Plus Extreme Learning Machine |
Abstract | ||
|---|---|---|
In this paper, a novel recognition algorithm based on discriminant tensor subspace analysis (DTSA) and extreme learning machine (ELM) is introduced. DTSA treats a gray facial image as a second order tensor and adopts two-sided transformations to reduce dimensionality. One of the many advantages of DTSA is its ability to preserve the spatial structure information of the images. In order to deal with micro-expression video clips, we extend DTSA to a high-order tensor. Discriminative features are generated using DTSA to further enhance the classification performance of ELM classifier. Another notable contribution of the proposed method includes significant improvements in face and micro-expression recognition accuracy. The experimental results on the ORL, Yale, YaleB facial databases and CASME micro-expression database show the effectiveness of the proposed method. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/s11063-013-9288-7 | Neural Processing Letters |
Keywords | Field | DocType |
Face recognition,Micro-expression recognition,Locality preserving projection,Discriminant information,Tensor subspace,Extreme learning machine | Tensor,Extreme learning machine,Computer science,Artificial intelligence,Classifier (linguistics),Discriminative model,Facial recognition system,Subspace topology,Pattern recognition,Discriminant,Curse of dimensionality,Speech recognition,Machine learning | Journal |
Volume | Issue | ISSN |
39 | 1 | 1370-4621 |
Citations | PageRank | References |
36 | 1.08 | 39 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sujing Wang | 1 | 690 | 37.65 |
| Hui-Ling Chen | 2 | 184 | 9.24 |
| Wen-Jing Yan | 3 | 265 | 9.43 |
| Yu-Hsin Chen | 4 | 836 | 37.69 |
| Xiaolan Fu | 5 | 786 | 60.72 |