Scipediacontent: Scipediacontent moved page Draft Content 310781680 to Liptrott et al 2019a

2021-02-01T22:47:08Z

Scipediacontent moved page Draft Content 310781680 to Liptrott et al 2019a

Scipediacontent: Created page with " == Abstract == In urban environments there are daily issues of traffic congestion which city authorities need to address. Realtime analysis of traffic flow information is cr..."

2021-02-01T22:47:04Z

Created page with " == Abstract == In urban environments there are daily issues of traffic congestion which city authorities need to address. Realtime analysis of traffic flow information is cr..."

New page

== Abstract ==

In urban environments there are daily issues of traffic congestion which city authorities need to address. Realtime analysis of traffic flow information is crucial for efficiently managing urban traffic. This paper aims to conduct traffic analysis using UAV-based videos and deep learning techniques. The road traffic video is collected by using a position-fixed UAV. The most recent deep learning methods are applied to identify the moving objects in videos. The relevant mobility metrics are calculated to conduct traffic analysis and measure the consequences of traffic congestion. The proposed approach is validated with the manual analysis results and the visualization results. The traffic analysis process is real-time in terms of the pre-trained model used.

== Original document ==

The different versions of the original document can be found in:

* [http://e-space.mmu.ac.uk/624465 http://e-space.mmu.ac.uk/624465]

* [https://e-space.mmu.ac.uk/624465/1/IWT4S_Submission_HZhang.pdf https://e-space.mmu.ac.uk/624465/1/IWT4S_Submission_HZhang.pdf]

* [http://xplorestaging.ieee.org/ielx7/8894828/8909819/08909879.pdf?arnumber=8909879 http://xplorestaging.ieee.org/ielx7/8894828/8909819/08909879.pdf?arnumber=8909879],
: [http://dx.doi.org/10.1109/avss.2019.8909879 http://dx.doi.org/10.1109/avss.2019.8909879]

* [https://dblp.uni-trier.de/db/conf/avss/avss2019.html#ZhangLBC19 https://dblp.uni-trier.de/db/conf/avss/avss2019.html#ZhangLBC19],
: [https://research.edgehill.ac.uk/en/publications/real-time-traffic-analysis-using-deep-learning-techniques-and-uav https://research.edgehill.ac.uk/en/publications/real-time-traffic-analysis-using-deep-learning-techniques-and-uav],
: [https://doi.org/10.1109/AVSS.2019.8909879 https://doi.org/10.1109/AVSS.2019.8909879],
: [https://academic.microsoft.com/#/detail/2989687024 https://academic.microsoft.com/#/detail/2989687024]

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Liptrott et al 2019a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 310781680 to Liptrott et al 2019a

Scipediacontent: Created page with " == Abstract == In urban environments there are daily issues of traffic congestion which city authorities need to address. Realtime analysis of traffic flow information is cr..."