Presenting the Multi-View Traffic Intersection Dataset (MTID): A Detailed Traffic-Surveillance Dataset

Morten Bornø Jensen, Andreas Møgelmose*, Thomas B. Moeslund

*Kontaktforfatter

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

2 Citationer (Scopus)
145 Downloads (Pure)

Abstrakt

This work presents a novel and unique traffic
surveillance dataset, the MTID. When capturing data for traffic
surveillance, the positioning of the camera is crucial, and
depending on the task different approaches provide different
advantages. Multiple viewpoints, however, are rarely compared.
Our dataset gives the ability to analyze the difference between
two viewpoints in great detail.
A complex traffic scene has been captured simultaneously
from two different viewpoints: that of a camera mounted on
existing infrastructure, and an that of a drone. The frames
from each video capture have been synchronized in time and
all road users have been carefully annotated down to pixellevel accuracy. The dataset consists of 3100 frames from each
viewpoint, containing 18883 individual annotations on the pole
viewpoint, and 50274 individual annotations on the drone
viewpoint. The dataset is freely available online*.
Apart from the dataset, which is our main contribution, we
also provide benchmark detection results for four different
groups of road users for other researchers to compare their
results with. We show that the detection problem is challenging,
as we achieve mAPs of only 22.62% and 27.75% using a pretrained state-of-the-art detector on the two viewpoints.
OriginalsprogEngelsk
TitelIEEE 23rd International Conference on Intelligent Transportation Systems 2020
Antal sider6
ForlagIEEE
Publikationsdato2020
Artikelnummer9294694
ISBN (Trykt)978-1-7281-4150-3
ISBN (Elektronisk)978-1-7281-4149-7
DOI
StatusUdgivet - 2020
Begivenhed23rd IEEE International Conference on Intelligent Transportation Systems 2020 -
Varighed: 20 sep. 202023 sep. 2020
https://ieee-itsc2020.org/

Konference

Konference23rd IEEE International Conference on Intelligent Transportation Systems 2020
Periode20/09/202023/09/2020
Internetadresse

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