Name
Abstract | ||
|---|---|---|
Human motion recognition is crucial for surveillance, search and rescue operation, smart homes, and senior care. In daily life, there exists various kinds of human motions with widely different characteristics and meanwhile they also exhibit some clustering features, which make it difficult for recognition. In this paper, a multiple-layer classification method is introduced for comprehensive human... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/JETCAS.2018.2797313 | IEEE Journal on Emerging and Selected Topics in Circuits and Systems |
Keywords | Field | DocType |
Spectrogram,Feature extraction,Ultra wideband radar,Legged locomotion,Doppler radar,Time-frequency analysis | Radar,Doppler radar,Search and rescue,Pattern recognition,Computer science,Spectrogram,Feature extraction,Real-time computing,Artificial intelligence,Time–frequency analysis,Cluster analysis,Principal component analysis | Journal |
Volume | Issue | ISSN |
8 | 2 | 2156-3357 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chuanwei Ding | 1 | 4 | 1.06 |
| Li Zhang | 2 | 2 | 0.78 |
| Chen Gu | 3 | 18 | 2.84 |
| Lei Bai | 4 | 0 | 0.34 |
| Zhicheng Liao | 5 | 0 | 0.34 |
| Hong Hong | 6 | 30 | 8.34 |
| Yusheng Li | 7 | 19 | 3.66 |
| Xiaohua Zhu | 8 | 46 | 9.50 |