Acta Optica Sinica, Volume. 39, Issue 7, 0715006(2019)

Stereo Matching Algorithm Based on Pixel Category Optimized PatchMatch

Yakun Gao, Tao Liu, Haibin Li*, and Wenming Zhang
Author Affiliations
  • Key Laboratory of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao, Hebei 066004, China
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    Figures & Tables(15)
    Detail comparison of algorithm content
    Comparison curves for different parameters of Geman-McClure function
    Grouping index. (a) Image cell index groups; (b) locally extended region
    Cross windows. (a) Expansion regions for different groups; (b) local image region
    Error matching rates of cross window and original method on test images
    Multi-category graphs. (a) Plastic; (b) Meanshift; (c) SNIC; (d) texture structure graph
    Improved local expansion movement algorithm
    Comparison of error rates between improved generation mechanism and the original method in one iteration
    Filling methods. (a) Texture region; (b) texture-less region. Red regions represent stable points, black regions represent unstable points, and white regions represent culling points
    Iterative optimization process. (a) LocalExp; (b) proposed algorithm
    Flow chart of proposed algorithm
    Optimization procedure of our algorithm
    Disparities of some global PatchMatch algorithms (points with error matching rate greater than 1 pixel are shown in red). (a) Image; (b) PMBP; (c) SPM-BP; (d) GCLSL; (e) PMSC; (f) LocalExp; (g) proposed
    • Table 1. Matching results of some PatchMatch based stereo algorithms in Midd2006 datasets with nonocc regions (threshold is 1 pixel, and the best results are shown in bold)

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      Table 1. Matching results of some PatchMatch based stereo algorithms in Midd2006 datasets with nonocc regions (threshold is 1 pixel, and the best results are shown in bold)

      ImagePMBPSPMBPGCLSLPMSCLocalExpProposed
      Aloe4.516.753.213.063.923.25
      Baby14.103.272.211.982.741.34
      Baby24.773.972.081.055.481.41
      Baby34.773.923.073.126.562.73
      Bowling114.1012.104.142.065.372.46
      Bowling24.645.272.191.456.441.99
      Cloth11.681.170.710.600.780.59
      Cloth43.102.201.751.870.990.98
      Flowerpots9.288.804.602.4910.894.01
      Lampshade113.508.6712.601.505.962.14
      Lampshade216.5017.2010.000.9921.701.08
      Midd137.4037.4034.9012.8030.806.07
      Midd238.4033.2032.904.3725.604.71
      Monopoly42.4032.7021.103.4628.044.97
      Plastic44.8035.2043.904.4040.103.34
      Rocks14.152.602.191.801.602.34
      Wood11.524.190.480.731.300.71
      Average14.6812.8510.702.8011.662.59
    • Table 2. Comparison of error rates between proposed method and LocalExp on Midd2003 datasets (threshold is 0.5 pixel)

      View table

      Table 2. Comparison of error rates between proposed method and LocalExp on Midd2003 datasets (threshold is 0.5 pixel)

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    Yakun Gao, Tao Liu, Haibin Li, Wenming Zhang. Stereo Matching Algorithm Based on Pixel Category Optimized PatchMatch[J]. Acta Optica Sinica, 2019, 39(7): 0715006

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    Paper Information

    Category: Machine Vision

    Received: Jan. 3, 2019

    Accepted: Apr. 1, 2019

    Published Online: Jul. 16, 2019

    The Author Email: Li Haibin (hbli@ysu.edu.cn)

    DOI:10.3788/AOS201939.0715006

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