A Comprehensive Review of RGBT Tracking

Zhang, H; Yuan, D; Shu, X; Li, Z; Liu, Q; Chang, X; He, Z; Shi, G

A Comprehensive Review of RGBT Tracking

Zhang, H Yuan, D Shu, X Li, Z Liu, Q Chang, X

He, Z Shi, G

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Publisher:: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Publication Type:: Journal Article
Citation:: IEEE Transactions on Instrumentation and Measurement, 2024, 73, (99)
Issue Date:: 2024-01-01

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Field	Value	Language
dc.contributor.author	Zhang, H
dc.contributor.author	Yuan, D
dc.contributor.author	Shu, X
dc.contributor.author	Li, Z
dc.contributor.author	Liu, Q
dc.contributor.author	Chang, X https://orcid.org/0000-0002-7778-8807
dc.contributor.author	He, Z
dc.contributor.author	Shi, G
dc.date.accessioned	2024-09-05T11:02:05Z
dc.date.available	2024-09-05T11:02:05Z
dc.date.issued	2024-01-01
dc.identifier.citation	IEEE Transactions on Instrumentation and Measurement, 2024, 73, (99)
dc.identifier.issn	0018-9456
dc.identifier.issn	1557-9662
dc.identifier.uri	http://hdl.handle.net/10453/180707
dc.description.abstract	RGBT tracking seeks to leverage both visible and thermal infrared images to enhance the robustness of target tracking. This method makes up for the limitations of single-sensor tracking. The RGB and thermal infrared images complement each other effectively, enabling the tracker to operate seamlessly in complex environments day and night. However, RGBT tracking still faces challenges, such as thermal crossover, occlusion (OCC), illumination changes, rapid target movement, and background clutter. These problems hinder the performance improvement of RGBT trackers. Researchers have proposed numerous RGBT tracking methods in response to these challenges over time. This article aims to comprehensively review and summarize the latest research progress in RGBT tracking. First, we categorize the existing tracing methods according to the RGBT tracing framework. Then, we introduce the datasets/benchmarks used to evaluate RGBT tracking methods. Subsequently, we present the results of representative tracking methods on multiple testing benchmarks, providing a more intuitive presentation of current research advances in the field of RGBT tracking. Finally, research directions are discussed to further advance the development of RGBT tracking.
dc.language	English
dc.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relation.ispartof	IEEE Transactions on Instrumentation and Measurement
dc.relation.isbasedon	10.1109/TIM.2024.3436098
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0299 Other Physical Sciences, 0906 Electrical and Electronic Engineering
dc.subject.classification	Electrical & Electronic Engineering
dc.subject.classification	4006 Communications engineering
dc.subject.classification	4008 Electrical engineering
dc.subject.classification	4009 Electronics, sensors and digital hardware
dc.title	A Comprehensive Review of RGBT Tracking
dc.type	Journal Article
utslib.citation.volume	73
utslib.for	0299 Other Physical Sciences
utslib.for	0906 Electrical and Electronic Engineering
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Strength - AAII - Australian Artificial Intelligence Institute
pubs.organisational-group	University of Technology Sydney/All Manual Groups
pubs.organisational-group	University of Technology Sydney/All Manual Groups/Australian Artificial Intelligence Institute (AAII)
utslib.copyright.status	closed_access	*
dc.date.updated	2024-09-05T11:02:01Z
pubs.issue	99
pubs.publication-status	Published
pubs.volume	73
utslib.citation.issue	99

Abstract:

RGBT tracking seeks to leverage both visible and thermal infrared images to enhance the robustness of target tracking. This method makes up for the limitations of single-sensor tracking. The RGB and thermal infrared images complement each other effectively, enabling the tracker to operate seamlessly in complex environments day and night. However, RGBT tracking still faces challenges, such as thermal crossover, occlusion (OCC), illumination changes, rapid target movement, and background clutter. These problems hinder the performance improvement of RGBT trackers. Researchers have proposed numerous RGBT tracking methods in response to these challenges over time. This article aims to comprehensively review and summarize the latest research progress in RGBT tracking. First, we categorize the existing tracing methods according to the RGBT tracing framework. Then, we introduce the datasets/benchmarks used to evaluate RGBT tracking methods. Subsequently, we present the results of representative tracking methods on multiple testing benchmarks, providing a more intuitive presentation of current research advances in the field of RGBT tracking. Finally, research directions are discussed to further advance the development of RGBT tracking.

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http://hdl.handle.net/10453/180707