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Laser & Optoelectronics Progress, Volume. 58, Issue 4, 0415003(2021)

Fast Reconstruction Algorithm of Point Cloud Implicit Surface

Lianzhe Wang1、*, Jungang Han1、*, Sheng Lu1, Haipeng Tang2, Quan Qi3, Ningyu Feng4, and Shaojie Tang5
Author Affiliations
  • 1School of Computer, Xi'an University of Posts and Telecommunications, Xi’an, Shaanxi, 710121, China
  • 2School of Computing Sciences and Computer Engineering, University of Southern Mississippi, Hattiesburg, Mississippi, 39406, China
  • 3College of Information Science and Technology, Shihezi University, Shihezi, Xinjiang, 832000, China
  • 4Otolaryngological Wards, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, 750004, China
  • 5School of Automation, Xi’an University of Posts and Telecommunications, Xi’an, Shaanxi, 710121, China
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    AbstractGet PDF(in Chinese)
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    References (16)
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    Figures & Tables(12)
    Flow chart of fast reconstruction algorithm for point cloud implicit surface

    Fig. 1. Flow chart of fast reconstruction algorithm for point cloud implicit surface

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    Interpolation process of point C in space

    Fig. 2. Interpolation process of point C in space

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    Surface area of point cloud

    Fig. 3. Surface area of point cloud

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    Statistical filtering and denoising flow chart

    Fig. 4. Statistical filtering and denoising flow chart

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    Facial point cloud and head point cloud are shown. (a) Facial point cloud positive perspective; (b) right perspective of facial point cloud; (c) head point cloud frontal view; (d) side view of head point cloud; (e) left view of Bunny point cloud; (f) right view of Bunny point cloud

    Fig. 5. Facial point cloud and head point cloud are shown. (a) Facial point cloud positive perspective; (b) right perspective of facial point cloud; (c) head point cloud frontal view; (d) side view of head point cloud; (e) left view of Bunny point cloud; (f) right view of Bunny point cloud

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    Head point cloud reconstruction results contrast. (a)(c) Reconstruction result of method in Ref. [6]; (b)(d) reconstruction result when interval step size of algorithm in this paper is set to 6

    Fig. 6. Head point cloud reconstruction results contrast. (a)(c) Reconstruction result of method in Ref. [6]; (b)(d) reconstruction result when interval step size of algorithm in this paper is set to 6

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    Comparison of head point cloud interpolation results in scatter plots. (a) Interpolation result of original RBF algorithm; (b) interpolation result of algorithm in this paper

    Fig. 7. Comparison of head point cloud interpolation results in scatter plots. (a) Interpolation result of original RBF algorithm; (b) interpolation result of algorithm in this paper

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    Facial point cloud interpolation and reconstruction results were obtained by using the method in Ref.[6]. (a) Interpolation result of facial point cloud data; (b) reconstruction result of facial point cloud surface

    Fig. 8. Facial point cloud interpolation and reconstruction results were obtained by using the method in Ref.[6]. (a) Interpolation result of facial point cloud data; (b) reconstruction result of facial point cloud surface

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    Interpolation and reconstruction results of the proposed algorithm. (a) Interpolation result of the proposed algorithm; (b) surface reconstruction result of algorithm in this paper; (c) local magnification of facial point cloud surface reconstruction result; (d) surface reconstruction result of Stanford Bunny point cloud

    Fig. 9. Interpolation and reconstruction results of the proposed algorithm. (a) Interpolation result of the proposed algorithm; (b) surface reconstruction result of algorithm in this paper; (c) local magnification of facial point cloud surface reconstruction result; (d) surface reconstruction result of Stanford Bunny point cloud

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    Curves of reconstruction time and deviation of point cloud data surface at different sampling step sizes. (a)Curve of point cloud on head; (b) curve of point cloud on face

    Fig. 10. Curves of reconstruction time and deviation of point cloud data surface at different sampling step sizes. (a)Curve of point cloud on head; (b) curve of point cloud on face

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    Deviation evaluation diagram of point cloud interpolation results in ImageWare. (a) Head point cloud; (b) positive view of facial point cloud; (c) side view of facial point cloud

    Fig. 11. Deviation evaluation diagram of point cloud interpolation results in ImageWare. (a) Head point cloud; (b) positive view of facial point cloud; (c) side view of facial point cloud

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    • Table 1. Interpolation operation time of point cloud data selected in experiment

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      Table 1. Interpolation operation time of point cloud data selected in experiment

      Point cloudSampling intervalNumber of RBF interpolation pointsNumber of trilinear interpolation pointsTotal number of pointsRBF interpolation time /sTime spent on trilinear interpolation /sTotal interpolation time /s
      Face14226004437350.1784050.1780
      22112039352625856.76630.07096.8372
      41056047493601662.21150.07392.2854
      Head135360516414.6615014.6615
      21768387772736.29750.01726.3147
      4884447969915.37460.01835.3929
      Bunny1412005991111.26060111.2606
      220514499843915.27530.145115.5508
      41026519681115.04700.24105.4304
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    Lianzhe Wang, Jungang Han, Sheng Lu, Haipeng Tang, Quan Qi, Ningyu Feng, Shaojie Tang. Fast Reconstruction Algorithm of Point Cloud Implicit Surface[J]. Laser & Optoelectronics Progress, 2021, 58(4): 0415003

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    Paper Information

    Category: Machine Vision

    Received: Jun. 8, 2020

    Accepted: Aug. 11, 2020

    Published Online: Feb. 4, 2021

    The Author Email: Wang Lianzhe (hjg@xupt.edu.cn), Han Jungang (hjg@xupt.edu.cn)

    DOI:10.3788/LOP202158.0415003

    Topics

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