Efficient Online Tracking-by-Detection With Kalman Filter

Visual tracking of multiple objects in videos has a promisingly broad application in manufacturing, construction, traffic, logistics, etc., especially in large-scale applications where it is not feasible to attach markers to many objects for traditional, marker-enabled tracking methods. This paper p...

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Autores principales:	Siyuan Chen, Chenhui Shao
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Computer vision Kalman filter multi-object tracking tracking-by-detection online tracking transportation Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/807ee0cd564647518945ab0208c3029e
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id	oai:doaj.org-article:807ee0cd564647518945ab0208c3029e
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spelling	oai:doaj.org-article:807ee0cd564647518945ab0208c3029e2021-11-18T00:05:21ZEfficient Online Tracking-by-Detection With Kalman Filter2169-353610.1109/ACCESS.2021.3124705https://doaj.org/article/807ee0cd564647518945ab0208c3029e2021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9597516/https://doaj.org/toc/2169-3536Visual tracking of multiple objects in videos has a promisingly broad application in manufacturing, construction, traffic, logistics, etc., especially in large-scale applications where it is not feasible to attach markers to many objects for traditional, marker-enabled tracking methods. This paper presents a new approach, Kalman-intersection-over-union (KIOU) tracker, for multi-object tracking in videos that integrates a Kalman filter with IOU-based track association methods. The performance of the proposed KIOU tracker is quantitatively evaluated with UA-DETRAC, an open real-world multi-object detection and tracking benchmark. Experimental results show that the KIOU tracker outperforms the leading tracking methods. Additionally, the KIOU tracker has speed comparable to simple area overlap-based track association and quality close to methods with much higher computational costs, demonstrating its potential for online, real-time multi-object tracking.Siyuan ChenChenhui ShaoIEEEarticleComputer visionKalman filtermulti-object trackingtracking-by-detectiononline trackingtransportationElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 147570-147578 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Computer vision Kalman filter multi-object tracking tracking-by-detection online tracking transportation Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Computer vision Kalman filter multi-object tracking tracking-by-detection online tracking transportation Electrical engineering. Electronics. Nuclear engineering TK1-9971 Siyuan Chen Chenhui Shao Efficient Online Tracking-by-Detection With Kalman Filter
description	Visual tracking of multiple objects in videos has a promisingly broad application in manufacturing, construction, traffic, logistics, etc., especially in large-scale applications where it is not feasible to attach markers to many objects for traditional, marker-enabled tracking methods. This paper presents a new approach, Kalman-intersection-over-union (KIOU) tracker, for multi-object tracking in videos that integrates a Kalman filter with IOU-based track association methods. The performance of the proposed KIOU tracker is quantitatively evaluated with UA-DETRAC, an open real-world multi-object detection and tracking benchmark. Experimental results show that the KIOU tracker outperforms the leading tracking methods. Additionally, the KIOU tracker has speed comparable to simple area overlap-based track association and quality close to methods with much higher computational costs, demonstrating its potential for online, real-time multi-object tracking.
format	article
author	Siyuan Chen Chenhui Shao
author_facet	Siyuan Chen Chenhui Shao
author_sort	Siyuan Chen
title	Efficient Online Tracking-by-Detection With Kalman Filter
title_short	Efficient Online Tracking-by-Detection With Kalman Filter
title_full	Efficient Online Tracking-by-Detection With Kalman Filter
title_fullStr	Efficient Online Tracking-by-Detection With Kalman Filter
title_full_unstemmed	Efficient Online Tracking-by-Detection With Kalman Filter
title_sort	efficient online tracking-by-detection with kalman filter
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/807ee0cd564647518945ab0208c3029e
work_keys_str_mv	AT siyuanchen efficientonlinetrackingbydetectionwithkalmanfilter AT chenhuishao efficientonlinetrackingbydetectionwithkalmanfilter
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Efficient Online Tracking-by-Detection With Kalman Filter

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