Cited by 305Video Surveillance and Tracking MethodsAutonomous Vehicle Technology and SafetyAdvanced Neural Network Applications

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Overview and methods of correlation filter algorithms in object tracking

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Liu, Shuai, Liu, Dongye, Srivastava, Gautam, Połap, Dawid, Woźniak, Marcin·2021·Complex & Intelligent Systems

DOI 10.1007/s40747-020-00161-4

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Abstract

Abstract An important area of computer vision is real-time object tracking, which is now widely used in intelligent transportation and smart industry technologies. Although the correlation filter object tracking methods have a good real-time tracking effect, it still faces many challenges such as scale variation, occlusion, and boundary effects. Many scholars have continuously improved existing methods for better efficiency and tracking performance in some aspects. To provide a comprehensive understanding of the background, key technologies and algorithms of single object tracking, this article focuses on the correlation filter-based object tracking algorithms. Specifically, the background and current advancement of the object tracking methodologies, as well as the presentation of the main datasets are introduced. All kinds of methods are summarized to present tracking results in various vision problems, and a visual tracking method based on reliability is observed.

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Authors: Liu, S., Liu, D., Srivastava, G., Połap, D., & Woźniak, M.
Affiliations: Hunan Normal University (CN)
Inner Mongolia University (CN)
China Medical University (TW)
Silesian University of Technology (PL)
Corresponding author: Srivastava, Gautam
ORCID: Liu, Shuai
Srivastava, Gautam
Połap, Dawid
Woźniak, Marcin
Venue: Complex & Intelligent Systems
Publisher: Springer Science and Business Media LLC
Published: 2020-06-09
Volume: 7
Issue: 4
Pages: 1895-1917
ISSN: 2198-6053 (ISSN-L)
2199-4536
DOI: 10.1007/s40747-020-00161-4
OpenAlex: W3034326629
Cited by: 305
References: 37
Citations by year: 2026: 5 · 2025: 19 · 2024: 27 · 2023: 36 · 2022: 83 · 2021: 106 · 2020: 26
FWCI: 24.40
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0 (tdm)
creativecommons.org/licenses/by/4.0 (vor)
Locations: Complex & Intelligent Systems (publishedVersion, cc-by)
Funders: Zhejiang University
State Key Laboratory of Computer Aided Design and Computer Graphics
Science and Technology Program of Hunan Province
Topics: Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Video Surveillance and Tracking Methods
Physical Sciences › Engineering › Automotive Engineering › Autonomous Vehicle Technology and Safety
Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
Keywords: correlation filter, single object tracking, real-time object tracking, scale variation, occlusion, edge effects, tracking dataset

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Overview and methods of correlation filter algorithms in object tracking

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