Various shadows are one of main factors that cause errors in vision based vehicle detection. In this paper, two simple methods, land mark based method and BS & Edge method, are proposed for vehicle detection and shadow rejection. In the experiments, the accuracy of vehicle detection is higher than 98%, during which the shadows arisen from roadside buildings grew considerably. Based on these two methods, vehicle counting, tracking, classification, and speed estimation are achieved so that real-time traffic parameters concerning traffic flow can be extracted to describe the load of each lane.
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Mei YU, Yong-Deak KIM, "Vision Based Vehicle Detection and Traffic Parameter Extraction" in IEICE TRANSACTIONS on Fundamentals,
vol. E84-A, no. 6, pp. 1461-1470, June 2001, doi: .
Abstract: Various shadows are one of main factors that cause errors in vision based vehicle detection. In this paper, two simple methods, land mark based method and BS & Edge method, are proposed for vehicle detection and shadow rejection. In the experiments, the accuracy of vehicle detection is higher than 98%, during which the shadows arisen from roadside buildings grew considerably. Based on these two methods, vehicle counting, tracking, classification, and speed estimation are achieved so that real-time traffic parameters concerning traffic flow can be extracted to describe the load of each lane.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e84-a_6_1461/_p
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@ARTICLE{e84-a_6_1461,
author={Mei YU, Yong-Deak KIM, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Vision Based Vehicle Detection and Traffic Parameter Extraction},
year={2001},
volume={E84-A},
number={6},
pages={1461-1470},
abstract={Various shadows are one of main factors that cause errors in vision based vehicle detection. In this paper, two simple methods, land mark based method and BS & Edge method, are proposed for vehicle detection and shadow rejection. In the experiments, the accuracy of vehicle detection is higher than 98%, during which the shadows arisen from roadside buildings grew considerably. Based on these two methods, vehicle counting, tracking, classification, and speed estimation are achieved so that real-time traffic parameters concerning traffic flow can be extracted to describe the load of each lane.},
keywords={},
doi={},
ISSN={},
month={June},}
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TY - JOUR
TI - Vision Based Vehicle Detection and Traffic Parameter Extraction
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1461
EP - 1470
AU - Mei YU
AU - Yong-Deak KIM
PY - 2001
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E84-A
IS - 6
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - June 2001
AB - Various shadows are one of main factors that cause errors in vision based vehicle detection. In this paper, two simple methods, land mark based method and BS & Edge method, are proposed for vehicle detection and shadow rejection. In the experiments, the accuracy of vehicle detection is higher than 98%, during which the shadows arisen from roadside buildings grew considerably. Based on these two methods, vehicle counting, tracking, classification, and speed estimation are achieved so that real-time traffic parameters concerning traffic flow can be extracted to describe the load of each lane.
ER -