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The Study of Improved Particle Filtering Target Tracking Algorithm Based on Multi-features Fusion

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Artificial Intelligence Trends in Intelligent Systems (CSOC 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 573))

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Abstract

In view of the shortcomings of traditional particle filter which is lacking of utilizing current observational information, this paper proposes a multi-featured fusion tracking algorithm based on simulated annealing to improve particle filter. The proposed method solves the problem of large amount of computation and lack of particle number in high dimensional state. A hierarchical random search annealing method is used to generate a better proposal distribution in the Monte Carlo importance sampling. In the likelihood approximation, this paper integrated image feature attribute of colors and edges to generate weight function in the different annealing layer by weighting. Using this method to track the moving objects with complex background and occlusion, the experimental results show that the proposed method has high tracking accuracy and strong stability.

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Acknowledgments

This research was supported by the project of research foundation of the talent of scientific and technical innovation of Harbin City (NO. 2014RFQXJ103).

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Authors and Affiliations

  1. College of Automation, Harbin Engineering University, Harbin, Heilongjiang, China

    Hongxia Chu & Fanming Liu

  2. College of Electrical and Information Engineering, Heilongjiang Institute of Technology, Harbin, Heilongjiang, China

    Hongxia Chu, Zhongyu Xie, Du Juan & Rongyi Zhang

Authors
  1. Hongxia Chu
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  2. Zhongyu Xie
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  3. Du Juan
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  4. Rongyi Zhang
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  5. Fanming Liu
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Corresponding author

Correspondence to Hongxia Chu .

Editor information

Editors and Affiliations

  1. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlin, Czech Republic

    Radek Silhavy

  2. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlin, Czech Republic

    Roman Senkerik

  3. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlin, Czech Republic

    Zuzana Kominkova Oplatkova

  4. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlin, Czech Republic

    Zdenka Prokopova

  5. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlin, Czech Republic

    Petr Silhavy

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Chu, H., Xie, Z., Juan, D., Zhang, R., Liu, F. (2017). The Study of Improved Particle Filtering Target Tracking Algorithm Based on Multi-features Fusion. In: Silhavy, R., Senkerik, R., Kominkova Oplatkova, Z., Prokopova, Z., Silhavy, P. (eds) Artificial Intelligence Trends in Intelligent Systems. CSOC 2017. Advances in Intelligent Systems and Computing, vol 573. Springer, Cham. https://doi.org/10.1007/978-3-319-57261-1_3

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  • DOI: https://doi.org/10.1007/978-3-319-57261-1_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-57260-4

  • Online ISBN: 978-3-319-57261-1

  • eBook Packages: EngineeringEngineering (R0)

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