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Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 36, 2019 No. 12
3864-3868

Self-adaptive scale feature fusion and model update tracking algorithm

Wang Rihong
Li Yongjun
Zhang Lifeng
School of Information & Control Engineering, Qingdao University of Technology, Qingdao Shandong 266520, China
DOI: 10.19734/j.issn.1001-3695.2018.07.0419

Abstract

In the kernel correlation filter tracking algorithm, in order to reduce the interference of background similarity and other clutter to the tracker, and to solve the problem of model updating under the different confidence degree of tracking results, this paper proposed a self-adaptive scale feature fusion and model update(SFMU) tracking algorithm. Through multi-feature fusion and scale variation strategy to improve the multi-feature scale kernel correlation filter, it used multi-peak detection to judge the overall oscillation degree of response map, then evaluated the confidence degree of the tracking result. The algorithm stopped updating model timely in the case of low confidence of the tracking results such as occlusion and deformation. In the high confidence model update, the algorithm introduced the initial model to the alignment operation to suppress model drift. Therefore, compared with the kernel correlation filter algorithm, this algorithm is more exact, and the stability is better in the target of scale variation, occlusion and deformation. The experimental results on the OTB-50 dataset show that the precision and success rate of the proposed algorithm are better than those of kernel correlation filter algorithm.

Foundation Support

国家自然科学基金资助项目(61502262)
山东省研究生教育创新计划资助项目(SDYY16023)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.07.0419
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 12
Section: Technology of Graphic & Image
Pages: 3864-3868
Serial Number: 1001-3695(2019)12-076-3864-05

Publish History

[2019-12-05] Printed Article

Cite This Article

王日宏, 李永珺, 张立锋. 自适应尺度特征融合与模型更新的跟踪算法 [J]. 计算机应用研究, 2019, 36 (12): 3864-3868. (Wang Rihong, Li Yongjun, Zhang Lifeng. Self-adaptive scale feature fusion and model update tracking algorithm [J]. Application Research of Computers, 2019, 36 (12): 3864-3868. )

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.

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