Overview and methods of correlation filter algorithms in object tracking
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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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A correlation-filtering-based tracking algorithm can track an object based on the characteristics of its appearance.
“By employing a correlation tracking algorithm, the system can track the object based the characteristics of its appearance [93].”
From A Survey of Video Surveillance Systems in Smart City (2023) · cites this paper as [93]
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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
- Venue
- Complex & Intelligent Systems
- Published
- 2020-06-09
- Volume
- 7
- Issue
- 4
- Pages
- 1895-1917
- ISSN
- 2198-6053 (ISSN-L)
- 2199-4536
- OpenAlex
- W3034326629
- Cited by
- 305
- References
- 37
- Citations by year
- 2026: 5 · 2025: 19 · 2024: 27 · 2023: 36 · 2022: 83 · 2021: 106 · 2020: 26 · 2018: 3
- FWCI
- 24.40
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- 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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