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Long-Term Tracking Algorithm Based on Kernelized Correlation Filter

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Proceedings of the Fifth Euro-China Conference on Intelligent Data Analysis and Applications (ECC 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 891))

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Abstract

KCF (Kernelized Correlation Filter) is a classical tracking algorithm based on correlation filter, which has good performance in short-term tracking. But when the object is partially or fully occluded, or disappeared in the view, KCF doesn’t work well. In this paper, a long-term tracking algorithm based on KCF is proposed. HOG (Histogram of Oriented Gradient) and LAB three-channel color information are employed to represent the object, and a re-detection module is added into the KCF tracking procedure. The peak ratio is introduced to control the start of the re-detection module, and a correlation filter model based on SURF feature points is re-learned to continuously track the occluded object. Experimental results on OTB dataset show that our algorithm has higher tracking accuracy than other five trackers, and is suitable for long-term tracking.

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Acknowledgments

The work is sponsored by the Shaanxi International Cooperation Exchange Funded Projects (2017KW-013, 2017KW-016), Graduate Creative Funds of Xi’an University of Posts and Telecommunications (CXJJ2017004).

Author information

Authors and Affiliations

  1. Center for Image and Information Processing, Xi’an University of Posts and Telecommunications, Xi’an, 710121, China

    Na Li, Lingfeng Wu & Daxiang Li

  2. Key Laboratory of Electronic Information Application Technology for Scene Investigation, Ministry of Public Security, Xi’an, 710121, China

    Na Li, Lingfeng Wu & Daxiang Li

  3. International Joint Research Center for Wireless Communication and Information Processing, Xi’an, 710121, China

    Na Li, Lingfeng Wu & Daxiang Li

Authors
  1. Na Li
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  2. Lingfeng Wu
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  3. Daxiang Li
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Corresponding authors

Correspondence to Na Li or Lingfeng Wu .

Editor information

Editors and Affiliations

  1. Department of Computer Science, VSB-Technical University of Ostrava, Ostrava, Czech Republic

    Pavel Krömer

  2. School of Automation, Xi’an University of Posts and Telecommunications, Xi’an, China

    Hong Zhang

  3. College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, China

    Yongquan Liang

  4. College of Information Science and Engineering, Fujian University of Technology, Fuzhou, Fujian, China

    Jeng-Shyang Pan

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Li, N., Wu, L., Li, D. (2019). Long-Term Tracking Algorithm Based on Kernelized Correlation Filter. In: Krömer, P., Zhang, H., Liang, Y., Pan, JS. (eds) Proceedings of the Fifth Euro-China Conference on Intelligent Data Analysis and Applications. ECC 2018. Advances in Intelligent Systems and Computing, vol 891. Springer, Cham. https://doi.org/10.1007/978-3-030-03766-6_84

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