Comprehensive Data Set for Automatic Single Camera Visual Speed Measurement
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F18%3APU127786" target="_blank" >RIV/00216305:26230/18:PU127786 - isvavai.cz</a>
Result on the web
<a href="https://www.fit.vut.cz/research/publication/11701/" target="_blank" >https://www.fit.vut.cz/research/publication/11701/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/TITS.2018.2825609" target="_blank" >10.1109/TITS.2018.2825609</a>
Alternative languages
Result language
angličtina
Original language name
Comprehensive Data Set for Automatic Single Camera Visual Speed Measurement
Original language description
In this paper, we focus on traffic camera calibration and visual speed measurement from a single monocular camera, which is an important task of visual traffic surveillance. Existing methods addressing this problem are hard to compare due to a lack of a common dataset with reliable ground truth. Therefore, it is not clear how the methods compare in various aspects and what are the factors affecting their performance. We captured a new dataset of 18 full-HD videos, each around one hour long, captured at 6 different locations. Vehicles in the videos (20 865 instances in total) are annotated with precise speed measurements from optical gates using LIDAR and verified with several reference GPS tracks. We made the dataset available for download and it contains the videos and metadata (calibration, lengths of features in image, annotations, etc.) for future comparison and evaluation. Camera calibration is the most crucial part of the speed measurement; therefore, we provide a brief overview of the methods and analyze a recently published method for fully automatic camera calibration and vehicle speed measurement and report the results on this dataset in detail.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/LQ1602" target="_blank" >LQ1602: IT4Innovations excellence in science</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
ISSN
1524-9050
e-ISSN
1558-0016
Volume of the periodical
2018
Issue of the periodical within the volume
99
Country of publishing house
US - UNITED STATES
Number of pages
11
Pages from-to
1633-1643
UT code for WoS article
000466933500005
EID of the result in the Scopus database
2-s2.0-85046804014