Multi-Perspective Vehicle Detection and Tracking: Challenges, Dataset, and Metrics

Jacob Velling Dueholm; Miklas Strøm Kristoffersen; Ravi K. Satzoda; Eshed Ohn-Bar; Thomas B. Moeslund; Mohan M. Trivedi

doi:10.1109/ITSC.2016.7795671

Multi-Perspective Vehicle Detection and Tracking: Challenges, Dataset, and Metrics

Jacob Velling Dueholm, Miklas Strøm Kristoffersen, Ravi K. Satzoda, Eshed Ohn-Bar, Thomas B. Moeslund, Mohan M. Trivedi

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

8 Citationer (Scopus)

Abstract

The research community has shown significant improvements
in both vision-based detection and tracking of vehicles,
working towards a high level understanding of on-road
maneuvers. Behaviors of surrounding vehicles in a highway
environment is found as an interesting starting point, of
why this dataset is introduced along with its challenges
and evaluation metrics. A vision-based multi-perspective
dataset is presented, containing a full panoramic view from
a moving platform driving on U.S. highways capturing
2704x1440 resolution images at 12 frames per second. The
dataset serves multiple purposes to be used as traditional
detection and tracking, together with tracking of vehicles
across perspectives. Each of the four perspectives have
been annotated, resulting in more than 4000 bounding boxes
in order to evaluate and compare novel methods.

Originalsprog	Engelsk
Titel	2016 IEEE 19th International Conference on Intelligent Transportation Systems
Forlag	IEEE
Publikationsdato	26 dec. 2016
Sider	959-964
Artikelnummer	575
ISBN (Elektronisk)	978-1-5090-1889-5
DOI	https://doi.org/10.1109/ITSC.2016.7795671
Status	Udgivet - 26 dec. 2016
Begivenhed	International Conference on Intelligent Transportation Systems - Convention Center, Windsor Oceanico Hotel, Rio de Janeiro, Brasilien Varighed: 1 nov. 2016 → 4 nov. 2016 Konferencens nummer: 19

Konference

Konference	International Conference on Intelligent Transportation Systems
Nummer	19
Lokation	Convention Center, Windsor Oceanico Hotel
Land/Område	Brasilien
By	Rio de Janeiro
Periode	01/11/2016 → 04/11/2016

Adgang til dokumentet

10.1109/ITSC.2016.7795671

AUB Link

Søg efter materialet i Aalborg Universitetsbiblioteks søgemaskine

Master
Dueholm, J. V.
01/09/2014 → 30/06/2016
Projekter: Projekt › Andet

Citationsformater

@inproceedings{ca927974d6f94728a1959d85469431be,

title = "Multi-Perspective Vehicle Detection and Tracking: Challenges, Dataset, and Metrics",

abstract = "The research community has shown significant improvementsin both vision-based detection and tracking of vehicles,working towards a high level understanding of on-roadmaneuvers. Behaviors of surrounding vehicles in a highwayenvironment is found as an interesting starting point, ofwhy this dataset is introduced along with its challengesand evaluation metrics. A vision-based multi-perspectivedataset is presented, containing a full panoramic view froma moving platform driving on U.S. highways capturing2704x1440 resolution images at 12 frames per second. Thedataset serves multiple purposes to be used as traditionaldetection and tracking, together with tracking of vehiclesacross perspectives. Each of the four perspectives havebeen annotated, resulting in more than 4000 bounding boxesin order to evaluate and compare novel methods.",

author = "Dueholm, {Jacob Velling} and Kristoffersen, {Miklas Str{\o}m} and Satzoda, {Ravi K.} and Eshed Ohn-Bar and Moeslund, {Thomas B.} and Trivedi, {Mohan M.}",

year = "2016",

month = dec,

day = "26",

doi = "10.1109/ITSC.2016.7795671",

language = "English",

pages = "959--964",

booktitle = "2016 IEEE 19th International Conference on Intelligent Transportation Systems",

publisher = "IEEE",

address = "United States",

note = "International Conference on Intelligent Transportation Systems, ITSC ; Conference date: 01-11-2016 Through 04-11-2016",

}

Dueholm, JV, Kristoffersen, MS, Satzoda, RK, Ohn-Bar, E, Moeslund, TB & Trivedi, MM 2016, Multi-Perspective Vehicle Detection and Tracking: Challenges, Dataset, and Metrics. i 2016 IEEE 19th International Conference on Intelligent Transportation Systems., 575, IEEE, s. 959-964, International Conference on Intelligent Transportation Systems, Rio de Janeiro, Brasilien, 01/11/2016. https://doi.org/10.1109/ITSC.2016.7795671

Multi-Perspective Vehicle Detection and Tracking: Challenges, Dataset, and Metrics. / Dueholm, Jacob Velling; Kristoffersen, Miklas Strøm; Satzoda, Ravi K. et al.
2016 IEEE 19th International Conference on Intelligent Transportation Systems. IEEE, 2016. s. 959-964 575.

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

TY - GEN

T1 - Multi-Perspective Vehicle Detection and Tracking

T2 - International Conference on Intelligent Transportation Systems

AU - Dueholm, Jacob Velling

AU - Kristoffersen, Miklas Strøm

AU - Satzoda, Ravi K.

AU - Ohn-Bar, Eshed

AU - Moeslund, Thomas B.

AU - Trivedi, Mohan M.

N1 - Conference code: 19

PY - 2016/12/26

Y1 - 2016/12/26

N2 - The research community has shown significant improvementsin both vision-based detection and tracking of vehicles,working towards a high level understanding of on-roadmaneuvers. Behaviors of surrounding vehicles in a highwayenvironment is found as an interesting starting point, ofwhy this dataset is introduced along with its challengesand evaluation metrics. A vision-based multi-perspectivedataset is presented, containing a full panoramic view froma moving platform driving on U.S. highways capturing2704x1440 resolution images at 12 frames per second. Thedataset serves multiple purposes to be used as traditionaldetection and tracking, together with tracking of vehiclesacross perspectives. Each of the four perspectives havebeen annotated, resulting in more than 4000 bounding boxesin order to evaluate and compare novel methods.

AB - The research community has shown significant improvementsin both vision-based detection and tracking of vehicles,working towards a high level understanding of on-roadmaneuvers. Behaviors of surrounding vehicles in a highwayenvironment is found as an interesting starting point, ofwhy this dataset is introduced along with its challengesand evaluation metrics. A vision-based multi-perspectivedataset is presented, containing a full panoramic view froma moving platform driving on U.S. highways capturing2704x1440 resolution images at 12 frames per second. Thedataset serves multiple purposes to be used as traditionaldetection and tracking, together with tracking of vehiclesacross perspectives. Each of the four perspectives havebeen annotated, resulting in more than 4000 bounding boxesin order to evaluate and compare novel methods.

U2 - 10.1109/ITSC.2016.7795671

DO - 10.1109/ITSC.2016.7795671

M3 - Article in proceeding

SP - 959

EP - 964

BT - 2016 IEEE 19th International Conference on Intelligent Transportation Systems

PB - IEEE

Y2 - 1 November 2016 through 4 November 2016

ER -

Multi-Perspective Vehicle Detection and Tracking: Challenges, Dataset, and Metrics

Abstract

Konference

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Master

Citationsformater