Pedestrian Behavior Recognition Based on Improved Dual-stream Network with Differential Feature in Surveillance Video

Yonghong Tan, Xuebin Zhou, Aiwu Chen, Songqing Zhou, Yi-Zhang Jiang
2021 Scientific Programming  
In order to improve the pedestrian behavior recognition accuracy of video sequences in complex background, an improved spatial-temporal two-stream network is proposed in this paper. Firstly, the deep differential network is used to replace the temporal-stream network so as to improve the representation ability and extraction efficiency of spatiotemporal features. Then, the improved Softmax loss function based on decision-making level feature fusion mechanism is used to train the model, which
more » ... retain the spatiotemporal characteristics of images between different network frames to a greater extent and reflect the action category of pedestrians more realistically. Simulation results show that the proposed improved network achieves 87% recognition accuracy on the self-built infrared dataset, and the computational efficiency is improved by 15.1%.
doi:10.1155/2021/3279957 fatcat:sh6dxvikfzglfoomsxoeig4dgm