Name
Abstract | ||
|---|---|---|
The number of traffic accident deaths caused by driving is increasing every year, in which the improper driving behaviors account for a large proportion of traffic accidents. To alert the driver's behaviors, we design a light and fast neural network (LFNN). On this basis, we construct a convolutional two-stream interactive network framework. One stream is used to acquire the spatial information of hand appearance; the other stream is used to obtain hand movement's temporal information. The features generated by the two streams are fused and classified through a short, interactive connection network. Our network structure has been tested on the CVRR-HANDS 3D data set. The accuracy reaches up to 96.5%, which obtains an obvious improvement compared with state of the art. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/ICDMW51313.2020.00079 | 2020 International Conference on Data Mining Workshops (ICDMW) |
Keywords | DocType | ISSN |
traffic accident,driving,two-stream,neural network | Conference | 2375-9232 |
ISBN | Citations | PageRank |
978-1-7281-9013-6 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yefan Zhou | 1 | 0 | 0.34 |
| Zhao Lv | 2 | 0 | 0.34 |
| Chaoqun Wang | 3 | 8 | 4.84 |
| Shengli Zhang | 4 | 1075 | 84.58 |