摘 要：一场突如其来的新冠疫情，对我国公共卫生制度体系及社会经济发展都造成了重大影响。由于新型冠状病毒很容易在人群之间传播，进而导致聚集性感染。针对此问题，提出了一种基于 YOLOv4-tiny 以及 DEEPSORT 算法的人流量检测及反馈应用。在训练模型时使用 vocc2012 数据集中含有人类的图像作为训练集，使得模型只对人类进行检测。
关键词：YOLOv4-tiny；目标检测；疫情；人群；DEEPSORT
DOI:10.19850/j.cnki.2096-4706.2021.14.019
中图分类号：TP391.4 文献标识码：A 文章编号：2096-4706（2021）14-0071-04
People Traffic Detection and Feedback Application Based on YOLOv4-tiny and DEEPSORT
HU Peipei, LI Dan
(Jincheng College of Sichuan University, Chengdu 611731, China)
Abstract: The sudden arrival of COVID-19 epidemic has had a major impact on China’s public health system and socio-economic development. Because the Corona virus spreads easily among crowd, so it easily leads to clustering infection. To solve this problem, a people traffic detection and feedback application based on YOLOv4-tiny and DEEPSORT algorithm is proposed. When training the model, the image containing human in the vocc2012 data set is used as the training set, so that the model can only detect human.
Keywords: YOLOv4-tiny; target detection; epidemic situation; crowd; DEEPSORT
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作者简介：胡培培（1999.06—），男，汉族，四川德阳人， 本科在读，研究方向：高级算法。