Name
Abstract | ||
|---|---|---|
With the development of human-computer interaction, gesture recognition has gradually become one of the research hotspots. The cost reduction and the richer information of RGB-D images make the research of gesture recognition based on RGB-D images more and more. However, the current gesture processing methods for RGB-D images still can not fully utilize the information contained Aiming at the above problems, this paper studies the feature extraction method of RGB-D image, and proposes a multimodal and multilevel feature extraction method. By extracting multimodal and multilevel image features for mapping and splicing, the utilization of RGB-D image information and the accuracy in recognition are improved effectively. Finally, the experiments verified the effectiveness and robustness of the proposed method based on the self-built gesture database. Compared and analyzed with several other RGB-D processing methods, the processing method of this paper is more advanced and effective, and can achieve better results in gesture recognition. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.3233/JIFS-179541 | JOURNAL OF INTELLIGENT & FUZZY SYSTEMS |
Keywords | DocType | Volume |
Gesture recognition,RGB-D image,multilevel and multimodal fusion,feature extraction | Journal | 38 |
Issue | ISSN | Citations |
SP3.0 | 1064-1246 | 0 |
PageRank | References | Authors |
0.34 | 0 | 9 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jinrong Tian | 1 | 1 | 1.02 |
| Wentao Cheng | 2 | 8 | 1.11 |
| Ying Sun | 3 | 291 | 40.03 |
| Gongfa Li | 4 | 239 | 43.45 |
| Du Jiang | 5 | 97 | 14.40 |
| Guozhang Jiang | 6 | 172 | 27.25 |
| Bo Tao | 7 | 0 | 0.34 |
| Haoyi Zhao | 8 | 0 | 0.34 |
| Disi Chen | 9 | 39 | 7.70 |