Name
Abstract | ||
|---|---|---|
We propose a novel bimodal emotion recognition approach by using the boosting-based framework, in which we can automatically determine the adaptive weights for audio and visual features. In this way, we balance the dominances of audio and visual features dynamically in feature-level to obtain better performance. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-74889-2_71 | ACII |
Keywords | Field | DocType |
bimodal emotion recognition,novel bimodal emotion recognition,adaptive weight,boosting-based framework,visual feature,combining audio,better performance,visual features dynamically | Communication,Emotion recognition,Computer science,Speech recognition,Boosting (machine learning) | Conference |
Volume | ISSN | Citations |
4738 | 0302-9743 | 4 |
PageRank | References | Authors |
0.45 | 9 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lixing Huang | 1 | 113 | 8.89 |
| Le Xin | 2 | 25 | 2.33 |
| Liyue Zhao | 3 | 67 | 4.71 |
| Jianhua Tao | 4 | 848 | 138.00 |