AIC2018报告:交通监控研究

2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) Pub Date : 2018-06-01 DOI:10.1109/CVPRW.2018.00019

Tingyu Mao, Wei Zhang, Haoyu He, Yanjun Lin, Vinay Kale, Alexander Stein, Z. Kostić

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引用次数: 12

摘要

交通监控和管理技术是智慧城市应用中最有趣的一些方面。在本文中，我们研究并介绍了NVIDIA AI城市挑战赛2018 (AIC2018)的车辆检测、跟踪、速度估计和异常检测方法。我们在轨道1中应用了Mask-RCNN和deep-sort进行车辆检测和跟踪，在轨道2中应用了基于光流的方法。在轨道1中，我们实现了100%的检测率和7.97英里/小时的速度估计误差。

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AIC2018 Report: Traffic Surveillance Research

Traffic surveillance and management technologies are some of the most intriguing aspects of smart city applications. In this paper, we investigate and present the methods for vehicle detections, tracking, speed estimation and anomaly detection for NVIDIA AI City Challenge 2018 (AIC2018). We applied Mask-RCNN and deep-sort for vehicle detection and tracking in track 1, and optical flow based method in track 2. In track 1, we achieve 100% detection rate and 7.97 mile/hour estimation error for speed estimation.

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来源期刊

2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

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