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Laser & Optoelectronics Progress, Volume. 58, Issue 8, 0815008(2021)

Video Foreground-Background Separation via Weighted Schatten-p Norm and Structured Sparsity Decomposition

Yufeng Wei1, Mingli Jing1、*, Lan Li2, Kun Sun1, and Ruibo Fan1
Author Affiliations
  • 1School of Electronic Engineering, Xi'an Shiyou University, Xi'an, Shaanxi 710065, China
  • 2School of Science, Xi'an Shiyou University, Xi'an, Shaanxi 710065, China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (5)
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    References (25)
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    Figures & Tables(5)
    Structured figures based on 3 pixel×3 pixel overlapping group. (a)(b) Two different foreground distributions; (c)(d) overlapping group of two different distributions

    Fig. 1. Structured figures based on 3 pixel×3 pixel overlapping group. (a)(b) Two different foreground distributions; (c)(d) overlapping group of two different distributions

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    Fmeasure values under the different C values on Airport dataset

    Fig. 2. Fmeasure values under the different C values on Airport dataset

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    Results of six algorithms on nine sequences

    Fig. 3. Results of six algorithms on nine sequences

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    • Table 1. Information of 9 video datasets for comparison

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      Table 1. Information of 9 video datasets for comparison

      DatasetVideo resolution /(pixel×pixel)Scene feature
      Airport176×144Dynamic background, changing time information on the frame
      Bootstrap160×120Static background, some moving people in the room
      Curtain160×128Dynamic background, the curtains moving slowly and light change gradually
      SwitchLight160×128Dynamic background, light mutation
      WaterSurface160×128Dynamic background, water surface fluctuation
      Highway320×240Dynamic background, the high speed vehicle and the moving shadow
      Office360×240Static background, a people moving locally with strong light
      CamouFlage160×120Dynamic background, background with a changing screen
      WavingTrees160×120Dynamic background, the swinging branch

    • Table 2. Fmeasure values of six algorithms

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      Table 2. Fmeasure values of six algorithms

      VideoFmeasure
      GoDecLSDPCPWNNMWSNMProposed
      Airport0.66010.72730.66010.66010.61660.7103
      Bootstrap0.51100.51260.50880.50880.48660.5135
      Curtain0.83070.85960.83090.83070.82700.8614
      SwitchLight0.12680.78840.79660.79890.12900.1322
      WaterSurface0.87390.91700.86770.86610.84120.9096
      Highway0.80520.88620.88870.88940.81430.8869
      Office0.49130.46470.37770.37920.49430.4648
      CamouFlage0.00000.07670.11530.11460.00000.9487
      WavingTrees0.70570.72130.41290.41460.70810.7208
      Average0.55610.66150.60650.60690.54630.6831
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    Yufeng Wei, Mingli Jing, Lan Li, Kun Sun, Ruibo Fan. Video Foreground-Background Separation via Weighted Schatten-p Norm and Structured Sparsity Decomposition[J]. Laser & Optoelectronics Progress, 2021, 58(8): 0815008

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    Paper Information

    Category: Machine Vision

    Received: Sep. 30, 2020

    Accepted: Nov. 5, 2020

    Published Online: Apr. 16, 2021

    The Author Email: Jing Mingli (mljingsy@xsyu.edu.cn)

    DOI:10.3788/LOP202158.0815008

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology