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Laser & Optoelectronics Progress, Volume. 57, Issue 8, 081504(2020)

Stereo Matching by Improved Window Characteristics and Differential Operators

Xinchun Li1, Xinyong Yin1、*, and Sen Lin1,2,3
Author Affiliations
  • 1School of Electronic and Information Engineering, Liaoning Technical University, Huludao, Liaoning 125105, China
  • 2State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, Liaoning 110016, China
  • 3Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, Liaoning 110016, China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (14)
    Equations (0)
    References (20)
    Cited By (1)
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    Figures & Tables(14)
    Direct relevant neighborhood of matching points

    Fig. 1. Direct relevant neighborhood of matching points

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    Window shape and weight allocation

    Fig. 2. Window shape and weight allocation

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    Main flow chart of matching in this paper

    Fig. 3. Main flow chart of matching in this paper

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    Sample datasets diagrams (Jadeplant). (a) Left image; (b) right image; (c) ground truth; (d) mask

    Fig. 4. Sample datasets diagrams (Jadeplant). (a) Left image; (b) right image; (c) ground truth; (d) mask

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    Mismatching rate of different window shapes

    Fig. 5. Mismatching rate of different window shapes

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    Different types of matching windows

    Fig. 6. Different types of matching windows

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    Example of the effect improvement of proposed algorithm and the original method. (a) Left images; (b) ground truth images; (c) ELAS; (d) proposed algorithm

    Fig. 7. Example of the effect improvement of proposed algorithm and the original method. (a) Left images; (b) ground truth images; (c) ELAS; (d) proposed algorithm

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    bad index comparison

    Fig. 8. bad index comparison

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    avgErr index comparison chart

    Fig. 9. avgErr index comparison chart

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    Sample graphs of effectiveness improvement. (a) Left images; (b) ground truth; (c) GA-Net; (d) GwcNet; (e) Census; (f) SGM; (g) proposed algorithm

    Fig. 10. Sample graphs of effectiveness improvement. (a) Left images; (b) ground truth; (c) GA-Net; (d) GwcNet; (e) Census; (f) SGM; (g) proposed algorithm

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    Self-collecting images. (a) Left images; (b) GA-Net; (c) GwcNet; (d) Census; (e) SGM; (f) proposed algorithm

    Fig. 11. Self-collecting images. (a) Left images; (b) GA-Net; (c) GwcNet; (d) Census; (e) SGM; (f) proposed algorithm

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    • Table 1. Performance comparison of Gaussian weight window under two indices

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      Table 1. Performance comparison of Gaussian weight window under two indices

      Data nameEbad /%Eavg /%Data name
      ELASProposedELASProposed
      Adirondack12.07011.8900.8800.877Adirondack
      ArtL19.80019.2701.7601.630ArtL
      Jadeplant34.68034.6601.1701.170MotorcycleE
      MotorcycleE13.45013.2102.2102.080PianoL
      PianoL37.52036.5301.9601.930Pipes
      Pipes15.30014.7601.9001.800layroom
      Playroom26.68026.0404.5504.270Playtable
      Playtable26.38026.2900.9300.920PlaytableP
      PlaytableP14.84014.7400.8900.890Recycle
      Recycle17.85016.8500.9100.910Teddy
      Vintage33.69033.6602.4302.430Vintage

    • Table 2. Performance comparison of Scharr filter under two indices

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      Table 2. Performance comparison of Scharr filter under two indices

      Data nameEbad /%Eavg /%Data name
      ELASProposedELASProposed
      ArtL19.8019.730.880.86Adirondack
      Jadeplant34.6829.198.856.33Jadeplant
      MotorcycleE13.4513.091.171.13MotorcycleE
      Piano22.0421.922.212.22PianoL
      PianoL37.5237.501.961.97Pipes
      Pipes15.3015.190.930.92PlaytableP
      Playroom26.6825.630.910.89Teddy
      PlaytableP14.8414.79---
      Recycle17.8517.24---

    • Table 3. Performance comparison of proposed algorithm under two indices

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      Table 3. Performance comparison of proposed algorithm under two indices

      Data nameEbad /%Eavg /%Data name
      ELASProposedELASProposed
      Adirondack12.0711.810.880.83Adirondack
      ArtL19.8019.551.761.74ArtL
      Jadeplant34.6827.858.955.99Jadeplant
      MotorcycleE13.4513.301.171.15Motorcycle
      Piano22.0421.851.171.16MotorcycleE
      PianoL37.5236.032.211.94PianoL
      Pipes15.3015.301.961.94Pipes
      Playroom26.6825.630.930.92PlaytableP
      Recycle17.8517.121.971.92Shelves
      Teddy11.4210.880.910.83Teddy
      Vintage33.6932.332.432.39Vintage
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    Xinchun Li, Xinyong Yin, Sen Lin. Stereo Matching by Improved Window Characteristics and Differential Operators[J]. Laser & Optoelectronics Progress, 2020, 57(8): 081504

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    Paper Information

    Category: Machine Vision

    Received: Aug. 29, 2019

    Accepted: Sep. 24, 2019

    Published Online: Apr. 3, 2020

    The Author Email: Yin Xinyong (xin-yong.yin@outlook.com)

    DOI:10.3788/LOP57.081504

    Topics

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