Abstract
Pedestrian detection has always been a research hotspot and difficulty in the field of video analysis, and it has a wide range of applications in fields such as unmanned driving, road monitoring, and smart cities. Aiming at this problem, a pedestrian detection method based on the improved YOLOv3 algorithm is proposed. The software system is implemented and verified based on YOLO v3. Experimental results show that in pedestrian detection data sets such as the INRIA pedestrian data set, the accuracy of the algorithm is improved by 6.3% compared with the original algorithm. The target detection technology can meet the real-time performance and test requirements in terms of pedestrian accuracy. Finally, the future development and further research directions of pedestrian detection technology are discussed.
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