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

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

8 Citations (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.

Original language	English
Title of host publication	2016 IEEE 19th International Conference on Intelligent Transportation Systems
Publisher	IEEE
Publication date	26 Dec 2016
Pages	959-964
Article number	575
ISBN (Electronic)	978-1-5090-1889-5
DOIs	https://doi.org/10.1109/ITSC.2016.7795671
Publication status	Published - 26 Dec 2016
Event	International Conference on Intelligent Transportation Systems - Convention Center, Windsor Oceanico Hotel, Rio de Janeiro, Brazil Duration: 1 Nov 2016 → 4 Nov 2016 Conference number: 19

Conference

Conference	International Conference on Intelligent Transportation Systems
Number	19
Location	Convention Center, Windsor Oceanico Hotel
Country/Territory	Brazil
City	Rio de Janeiro
Period	01/11/2016 → 04/11/2016

Access to Document

10.1109/ITSC.2016.7795671

AUB Link

Search for the material in Aalborg University Library's search engine

Master of Science in Vision, Graphics and Interactive Systems
Dueholm, J. V.
01/09/2014 → 30/06/2016
Project: Other

Cite this

@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. in 2016 IEEE 19th International Conference on Intelligent Transportation Systems., 575, IEEE, pp. 959-964, International Conference on Intelligent Transportation Systems, Rio de Janeiro, Brazil, 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. p. 959-964 575.

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

TY - GEN

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T2 - International Conference on Intelligent Transportation Systems

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AU - Trivedi, Mohan M.

N1 - Conference code: 19

PY - 2016/12/26

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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.

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DO - 10.1109/ITSC.2016.7795671

M3 - Article in proceeding

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PB - IEEE

Y2 - 1 November 2016 through 4 November 2016

ER -

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

Abstract

Conference

Access to Document

AUB Link

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Projects

Master of Science in Vision, Graphics and Interactive Systems

Cite this