TY  - JOUR
PY  - 2022//
TI  - Scene recognition of road traffic accident based on an improved faster R-CNN algorithm
JO  - International journal of crashworthiness
A1  - Wang, Fenghui
A1  - Qiao, Jie
A1  - Li, Lingyi
A1  - Liu, Yongtao
A1  - Wei, Lang
SP  - 1428
EP  - 1432
VL  - 27
IS  - 5
N2  - Traffic accident scene recognition is the first premise of accident analysis and scene reconstruction, so the research on traffic accident scene recognition technology is of great significance. In this paper, an improved Region Proposal Network based on Faster Region-based Convolutional Network (Faster R-CNN) is proposed. Because the network adopts four strategies to improve the Regional Proposal Network (RPN), the network structure in this paper is called Multi-strategy Region Proposal Network (MSRPN). The experimental results show that the mAP value of MSRPN algorithm surpasses the other two target recognition algorithms. At the same time, MSRPN only needs to generate 150 region proposals in each image to obtain the above experimental results. In addition, the algorithm has good performance in small target detection. Especially, the target recognition speed is 6 fps, which is faster than other target detection algorithms. In conclusion, the target recognition algorithm based on MSRPN can be effectively applied to target recognition system.<p />  <p>Language: en</p>
LA  - en
SN  - 1358-8265
UR  - http://dx.doi.org/10.1080/13588265.2021.1959156
ID  - ref1
ER  -