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...
Saved in:
Main Authors: | , , , |
---|---|
Other Authors: | |
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2013
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/101922 http://hdl.handle.net/10220/12766 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-101922 |
---|---|
record_format |
dspace |
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 |
_version_ |
1681056233831792640 |