Vision-based vehicle queue detection at traffic junctions

Real-time traffic queue detection can directly aid in dynamic traffic light control at road junctions. In this paper, we propose an efficient technique to detect vehicle queue lengths at traffic junctions based on progressive block based image processing. We also propose a two-step approach for vehi...

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Main Authors: Srikanthan, Thambipillai, Satzoda, R. K., Suchitra, S., Chia, J. Y.
Other Authors: School of Computer Engineering
Format: Conference or Workshop Item
Language:English
Published: 2013
Subjects:
Online Access:https://hdl.handle.net/10356/101922
http://hdl.handle.net/10220/12766
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1019222020-05-28T07:41:41Z Vision-based vehicle queue detection at traffic junctions Srikanthan, Thambipillai Satzoda, R. K. Suchitra, S. Chia, J. Y. School of Computer Engineering IEEE Conference on Industrial Electronics and Applications (7th : 2012 : Singapore) DRNTU::Engineering::Computer science and engineering Real-time traffic queue detection can directly aid in dynamic traffic light control at road junctions. In this paper, we propose an efficient technique to detect vehicle queue lengths at traffic junctions based on progressive block based image processing. We also propose a two-step approach for vehicle detection that relies on edges and dark features in the image. It is shown that this vehicle detection approach is robust to heavy and light shadows. Further, the threshold adapts itself dynamically to handle varying light conditions. Evaluation of the proposed method using over 45 real video sequences shows nearly 100% accuracy in vehicle detection and queue length estimation. 2013-08-01T04:06:46Z 2019-12-06T20:46:40Z 2013-08-01T04:06:46Z 2019-12-06T20:46:40Z 2011 2011 Conference Paper https://hdl.handle.net/10356/101922 http://hdl.handle.net/10220/12766 10.1109/ICIEA.2012.6360703 en
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering
spellingShingle DRNTU::Engineering::Computer science and engineering
Srikanthan, Thambipillai
Satzoda, R. K.
Suchitra, S.
Chia, J. Y.
Vision-based vehicle queue detection at traffic junctions
description Real-time traffic queue detection can directly aid in dynamic traffic light control at road junctions. In this paper, we propose an efficient technique to detect vehicle queue lengths at traffic junctions based on progressive block based image processing. We also propose a two-step approach for vehicle detection that relies on edges and dark features in the image. It is shown that this vehicle detection approach is robust to heavy and light shadows. Further, the threshold adapts itself dynamically to handle varying light conditions. Evaluation of the proposed method using over 45 real video sequences shows nearly 100% accuracy in vehicle detection and queue length estimation.
author2 School of Computer Engineering
author_facet School of Computer Engineering
Srikanthan, Thambipillai
Satzoda, R. K.
Suchitra, S.
Chia, J. Y.
format Conference or Workshop Item
author Srikanthan, Thambipillai
Satzoda, R. K.
Suchitra, S.
Chia, J. Y.
author_sort Srikanthan, Thambipillai
title Vision-based vehicle queue detection at traffic junctions
title_short Vision-based vehicle queue detection at traffic junctions
title_full Vision-based vehicle queue detection at traffic junctions
title_fullStr Vision-based vehicle queue detection at traffic junctions
title_full_unstemmed Vision-based vehicle queue detection at traffic junctions
title_sort vision-based vehicle queue detection at traffic junctions
publishDate 2013
url https://hdl.handle.net/10356/101922
http://hdl.handle.net/10220/12766
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