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Technology of Graphic & Image
|
287-292

Dual-core KCF target tracking algorithm based on spatio-temporal saliency

Liu Xiaonana,b,c
Deng Chunhuaa,b,c
Ding Shenga,b,c
a. School of Computer Science & Technology, b. Hubei Province Key Laboratory of Intelligent Information Processing & Real-time Industrial System, c. University of Science & Technology, Big Data Science & Engineering Research Institute, Wuhan University of Science & Technology, Wuhan 430065, China

Abstract

The traditional KCF tracking algorithm is prone to the accumulation of tracking errors in template update, which leads to the tracking drift in the target tracking process. Aiming at this problem, this paper proposed a spatio-temporal significance dual-core KCF target tracking method. This algorithm introduced a spatio-temporal saliency method to search for the significant features of the target region and the local region with stable attitude. The local region was less sensitive to the cumulative errors in the tracking process, which could reduce the cumulative errors in the tracking process. Then, it established dual-core tracking mechanism combining source target and salient region. During the tracking process, the tracking results of the original target are constantly fine-tuned to reduce the cumulative tracking errors. In addition, aiming at the large offset of adjacent frames of fast-moving targets, this paper proposed an anchor point prediction mechanism, which made the tracking anchor closer to the target position and could track the target more accurately. The experimental results on large public data show that the proposed algorithm has strong adaptability in complex situations such as illumination, occlusion, deformation, fast motion, rotation and background clutter.

Foundation Support

湖北省科技厅计划项目(2018CFB195)
湖北省教育厅科学技术研究计划青年人才项目(Q20181104)
智能信息处理与实时工业系统湖北省重点实验室开放基金资助项目(znxx2018QN09)
武汉科技大学国防预研基金资助项目(GF201814)
国家自然科学基金资助项目(61806150,61702182)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.08.0574
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 1
Section: Technology of Graphic & Image
Pages: 287-292
Serial Number: 1001-3695(2021)01-058-0287-06

Publish History

[2021-01-05] Printed Article

Cite This Article

刘小楠, 邓春华, 丁胜. 基于时空显著性的双核KCF目标跟踪算法 [J]. 计算机应用研究, 2021, 38 (1): 287-292. (Liu Xiaonan, Deng Chunhua, Ding Sheng. Dual-core KCF target tracking algorithm based on spatio-temporal saliency [J]. Application Research of Computers, 2021, 38 (1): 287-292. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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