Tracking and Calculating Speed of Mixing Vehicles Using YOLOv4 and DeepSORT

P. N. Huu, BangLe Anh, Vu Tran Ngoc Nam, Tran Manh Hoang, Tien Dzung Nguyen, Q. Minh
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Abstract

Today, strong development of socio-economic has promoted participation in traffic. As a result, traffic management is becoming more and more difficult. To effectively solve the problem, artificial intelligence (AI) applications are applied for the improvement of urban traffic management and administration. Therefore, we propose an intelligent algorithm for monitoring and detecting vehicles. We use data collected from cameras and apply deep learning technology to track objects in the paper. The proposed algorithm uses YOLOv4 combined with DeepSORT for tracking and calculating the speed of detected vehicles. Results show that the proposed algorithm improves accuracy up to 95% which is suitable to apply for real applications.
基于YOLOv4和DeepSORT的混合车辆速度跟踪与计算
今天,社会经济的强劲发展促进了人们对交通的参与。因此,交通管理变得越来越困难。为了有效解决这一问题,人工智能(AI)应用被用于改善城市交通管理和行政。因此,我们提出了一种用于车辆监控和检测的智能算法。我们使用从相机收集的数据,并应用深度学习技术来跟踪论文中的物体。该算法使用YOLOv4结合DeepSORT对被检测车辆进行跟踪和速度计算。结果表明,该算法的准确率可达95%以上,适合于实际应用。
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