The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Diverses ombres sont l’un des principaux facteurs à l’origine d’erreurs dans la détection des véhicules par vision. Dans cet article, deux méthodes simples, la méthode basée sur les repères et la méthode BS & Edge, sont proposées pour la détection des véhicules et le rejet des ombres. Dans les expériences, la précision de la détection des véhicules est supérieure à 98 %, au cours de laquelle les ombres provenant des bâtiments en bordure de route ont considérablement augmenté. Sur la base de ces deux méthodes, le comptage, le suivi, la classification et l'estimation de la vitesse des véhicules sont réalisés afin que les paramètres de trafic en temps réel concernant le flux de circulation puissent être extraits pour décrire la charge de chaque voie.
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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},}
Copier
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 -