@inproceedings{ba77aefdf9494610be724223aa4c4e60,
title = "Array camera crowd counting method based on Yolov5",
abstract = "Array cameras can effectively balance the contradiction between large field of view and high resolution in existing imaging systems, and can effectively solve the problem of high-density crowd counting in large scenes such as stadiums and parks. In order to realize the intelligence of the array camera, a crowd counting method of the array camera based on yolov5 is proposed, which is of great significance to realize the intelligence of public security management. Through the rtsp video stream input by the array sub-camera, the position coordinate conversion relationship between the sub-image and the large image is established, and then the panoramic image is output in real time to meet the needs of video surveillance. Then preprocess each rtsp video stream, use the tensorrt-accelerated yolov5 target detection method to identify the target in each sub-image, and convert the target coordinates into the coordinates of the large image, and use the NMS method to filter out duplicate targets in the overlapping area of each sub-image., and finally summarize the results to output the target number. The system can be deployed on Win10, Linux and embedded system, working reliably with high precision to meet the practical application.",
keywords = "Yolov5, array camera, crowd counting, target detection",
author = "Xinzhen Zhang and Ming Liu and Mei Hui and Lingqin Kong",
note = "Publisher Copyright: {\textcopyright} 2022 SPIE.; Optoelectronic Imaging and Multimedia Technology IX 2022 ; Conference date: 05-12-2022 Through 11-12-2022",
year = "2022",
doi = "10.1117/12.2643955",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Qionghai Dai and Tsutomu Shimura and Zhenrong Zheng",
booktitle = "Optoelectronic Imaging and Multimedia Technology IX",
address = "United States",
}