Technology of Graphic & Image
|
App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 1
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
DOI: 10.19734/j.issn.1001-3695.2019.08.0574

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.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

Indexed & Evaluation

  • The Second National Periodical Award 100 Key Journals
  • Double Effect Journal of China Journal Formation
  • the Core Journal of China (Peking University 2023 Edition)
  • the Core Journal for Science
  • Chinese Science Citation Database (CSCD) Source Journals
  • RCCSE Chinese Core Academic Journals
  • Journal of China Computer Federation
  • 2020-2022 The World Journal Clout Index (WJCI) Report of Scientific and Technological Periodicals
  • Full-text Source Journal of China Science and Technology Periodicals Database
  • Source Journal of China Academic Journals Comprehensive Evaluation Database
  • Source Journals of China Academic Journals (CD-ROM Version), China Journal Network
  • 2017-2019 China Outstanding Academic Journals with International Influence (Natural Science and Engineering Technology)
  • Source Journal of Top Academic Papers (F5000) Program of China's Excellent Science and Technology Journals
  • Source Journal of China Engineering Technology Electronic Information Network and Electronic Technology Literature Database
  • Source Journal of British Science Digest (INSPEC)
  • Japan Science and Technology Agency (JST) Source Journal
  • Russian Journal of Abstracts (AJ, VINITI) Source Journals
  • Full-text Journal of EBSCO, USA
  • Cambridge Scientific Abstracts (Natural Sciences) (CSA(NS)) core journals
  • Poland Copernicus Index (IC)
  • Ulrichsweb (USA)