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Title	Pedestrian Detection Algorithm Based On Improved Yolo V3
ID_Doc	41532
Authors	Zhang J.; Chen X.; Li Y.; Chen T.; Mou L.
Year	2021
Published	2021 IEEE International Conference on Power, Intelligent Computing and Systems, ICPICS 2021
DOI	http://dx.doi.org/10.1109/ICPICS52425.2021.9524267
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. © 2021 IEEE.
Author Keywords	feature detection; Image recognition; Pedestrian detection; yolo v3

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