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An Improved Background Subtraction Method Based on ViBe

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Pattern Recognition (CCPR 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 662))

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Abstract

The classic ViBe method has shortcoming that it may detect the “Ghosting” area, when the initial frame contains a moving target or a target moves from a stationary position. In this paper, the Ghosting phenomenon was investigated, and an improved background subtraction method based on ViBe was proposed. The proposed method provided an enhanced pixel classification mechanism and background update mechanism, a significantly better Ghosting melting speed was obtained in the proposed method as compared to the classic ViBe method. The experimental results found that the proposed method had a good performance in static background scenes, and a low computational cost, that the proposed method can be used in real-time supervisory control system.

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Author information

Authors and Affiliations

  1. School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan, China

    Botao He

  2. Wuhan Research Institute of Posts and Telecommunications, Wuhan, China

    Shaohua Yu

Authors
  1. Botao He
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  2. Shaohua Yu
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Corresponding author

Correspondence to Botao He .

Editor information

Editors and Affiliations

  1. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Tieniu Tan

  2. Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, China

    Xuelong Li

  3. Chinese Academy of Sciences, Institute of Computing Technology, Beijing, China

    Xilin Chen

  4. Tsinghua University , Beijing, China

    Jie Zhou

  5. Nanjing University of Science and Technology, Nanjing, China

    Jian Yang

  6. University of Electronic Science and Technology, Chengdu, Sichuan, China

    Hong Cheng

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© 2016 Springer Nature Singapore Pte Ltd.

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He, B., Yu, S. (2016). An Improved Background Subtraction Method Based on ViBe. In: Tan, T., Li, X., Chen, X., Zhou, J., Yang, J., Cheng, H. (eds) Pattern Recognition. CCPR 2016. Communications in Computer and Information Science, vol 662. Springer, Singapore. https://doi.org/10.1007/978-981-10-3002-4_30

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  • DOI: https://doi.org/10.1007/978-981-10-3002-4_30

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3001-7

  • Online ISBN: 978-981-10-3002-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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