Research Article
Algorithm of Pedestrian Detection Based on YOLOv4
@INPROCEEDINGS{10.1007/978-3-031-50580-5_19, author={Qinjun Zhao and Kehua Du and Hang Yu and Shijian Hu and Rongyao Jing and Xiaoqiang Wen}, title={Algorithm of Pedestrian Detection Based on YOLOv4}, proceedings={Multimedia Technology and Enhanced Learning. 5th EAI International Conference, ICMTEL 2023, Leicester, UK, April 28-29, 2023, Proceedings, Part IV}, proceedings_a={ICMTEL PART 4}, year={2024}, month={2}, keywords={Deep learning Pedestrian detection YOLOv4 Soft-NMS}, doi={10.1007/978-3-031-50580-5_19} }- Qinjun Zhao
Kehua Du
Hang Yu
Shijian Hu
Rongyao Jing
Xiaoqiang Wen
Year: 2024
Algorithm of Pedestrian Detection Based on YOLOv4
ICMTEL PART 4
Springer
DOI: 10.1007/978-3-031-50580-5_19
Abstract
Pedestrian detection technology is applied to more and more scenes, which shows high application value. In recent years, with the development of electronic information technology, the computing speed of computers has been growing rapidly, and the deep learning technology has become better and better with the development of computers. In this paper, based on YOLOv4, this paper studied the scheme of pedestrian detection, obtained the anchor of the pedestrian data through the K-Means algorithm, the loss function of the target detection algorithm is optimized, and introduced the Soft-NMS to improve the pedestrian occlusion problem in detection. Through relevant model verification experiments, the algorithm in this paper is faster than the traditional target detection algorithm in terms of speed, accuracy and robustness.
