Name
Title | ||
|---|---|---|
Micro-Expression Recognition By Regression Model And Group Sparse Spatio-Temporal Feature Learning |
Abstract | ||
|---|---|---|
In this letter, a micro-expression recognition method is investigated by integrating both spatio-temporal facial features and a regression model. To this end, we first perform a multi-scale facial region division for each facial image and then extract a set of local binary patterns on three orthogonal planes ( LBP-TOP) features corresponding to divided facial regions of the micro-expression videos. Furthermore, we use GSLSR model to build the linear regression relationship between the LBP-TOP facial feature vectors and the micro expressions label vectors. Finally, the learned GSLSR model is applied to the prediction of the micro-expression categories for each test micro-expression video. Experiments are conducted on both CASME II and SMIC micro-expression databases to evaluate the performance of the proposed method, and the results demonstrate that the proposed method is better than the baseline micro-expression recognition method. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1587/transinf.2015EDL8221 | IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS |
Keywords | Field | DocType |
micro-expression recognition, local binary patterns on three orthogonal planes (LBP-TOP), group sparse least squares regression (GSLSR) | Pattern recognition,Facial expression recognition,Computer science,Regression analysis,Speech recognition,Artificial intelligence,Feature learning | Journal |
Volume | Issue | ISSN |
E99D | 6 | 1745-1361 |
Citations | PageRank | References |
4 | 0.38 | 9 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ping Lu | 1 | 5 | 1.07 |
| Wenming Zheng | 2 | 1240 | 80.70 |
| Ziyan Wang | 3 | 4 | 0.38 |
| qiang li | 4 | 8 | 7.55 |
| Yuan Zong | 5 | 162 | 17.39 |
| Minghai Xin | 6 | 55 | 5.70 |
| Lenan Wu | 7 | 700 | 62.18 |