Name
Abstract | ||
|---|---|---|
•A new fall event dataset in crowded and complex scenes is created.•A novel fall event detection architecture based on attention guided LSTM is proposed.•The experimental results show that the proposed method outperforms the state-of-the-art methods. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.patrec.2018.08.031 | Pattern Recognition Letters |
Keywords | Field | DocType |
Fall event detection,Fall event dataset,LSTM | Computer vision,Pedestrian,Pattern recognition,ALARM,Artificial intelligence,Mathematics,Bounding overwatch | Journal |
Volume | ISSN | Citations |
130 | 0167-8655 | 2 |
PageRank | References | Authors |
0.39 | 27 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qi Feng | 1 | 10 | 1.91 |
| Chenqiang Gao | 2 | 23 | 8.86 |
| Lan Wang | 3 | 9 | 2.19 |
| Yue Zhao | 4 | 58 | 28.59 |
| Tiecheng Song | 5 | 217 | 29.55 |
| Qiang Li | 6 | 4 | 1.08 |