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Denoising of point cloud data for computer-aided design, engineering, and manufacturing

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Abstract

In this review paper, we first introduce different sensors used in geometric sensing for obtaining the geometric information of various objects or parts. Next, two types of measurement errors are defined. Then, we discuss the existing methods for removing or correcting short-range and long-range measurement errors as well as noise at geometric discontinuity. Finally, some conclusions are drawn and future research directions are provided.

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References

  1. Klinger P, Veit K, Hausler G, Karbacher S, Laboureux X (2003) Optical 3D sensors for real applications—potentials and limits. Proceedings of the 8th International Rendez-vous for 3D Digitisation and Modeling Professionals. April 23–24, Paris, France, 1–5

  2. Bernardini F, Bajaj CL, Chen J, Schikore DR (1999) Automatic reconstruction of 3D CAD models from digital scans. Int J Comput Geometry Appl 9(4 & 5):327–369

    Article  Google Scholar 

  3. Varady T, Martin RR, Cox J (1997) Reverse engineering of geometric models—an introduction. Comput Aided Des 29(4):255–269

    Article  Google Scholar 

  4. Dorsch RG, Hausler G, Herrmann JM (1994) Laser triangulation: fundamental uncertainty in distance measurement. Appl Opt 33(7):1306–1314

    Article  Google Scholar 

  5. Chan HL, Mitchell JP, Spence AD, Sklad MP, Capson DW (2005) Laser digitizer/stereo vision methods for simultaneous measurement/analysis of sheet metal forming strain/geometry. ASME 2005 Int Mech Eng Congress Exposition. 237–246

  6. Shen J, Yoon D, Liu Y, Orady E (2007) A planar measurement error synthesizer for touch probes and laser sensors. Technical Report 2007–1, University of Michigan-Dearborn

  7. Rioux M, Bechthold G, Taylor D, Duggan M (1987) Design of a large depth of view three-dimensional camera for robot vision. Opt Eng 26(12):1245–1250

    Article  Google Scholar 

  8. Baribeau R, Rioux M (1991) Influence of speckle on laser range finders. Appl Opt 30(20):2873–2878

    Article  Google Scholar 

  9. Tamura S, Kim EK, Close R, Sato Y (1994) Error correction in laser scanner three-dimensional measurement by two-axis model and coarse-fine parameter search. Pattern Recogn 27(3):331–338

    Article  Google Scholar 

  10. Smith KB, Zheng YF (1998) Accuracy analysis of point laser triagulation probes using simulation. ASME J Manuf Sci Eng 120(4):736–745

    Article  Google Scholar 

  11. Feng H, Liu Y, Xi F (2001) Analysis of digitizing errors of a laser scanning system. Precision Eng 25(3):185–191

    Article  Google Scholar 

  12. Curless B, Levoy M (1995) Better optical triangulation through spacetime analysis. Proceedings of IEEE International Conference on Computer Vision ’95, 987–994

  13. Cederberg P, Olsson M, Bolmsjo G (2002) Virtual triangulation sensor development, behavior simulation and CAR integration applied to robotic arc-welding. J Intell Rob Syst 35(4):365–379

    Article  Google Scholar 

  14. Forest J, Salvi J, Cabruja E, Pous C (2004) Laser stripe peak detector for 3D scanners. A FIR filter approach. Proceedings of the 17th International Conference on Pattern Recognition. 3:646–649

  15. Xie H, McDonnell KT, Qin H (2004) Surface reconstruction of noisy and defective data sets. IEEE Visualization 259–266

  16. Kolluri R, Shewchuk JR, O’Brien JF (2004) Spectral surface reconstruction from noisy point clouds. Symposium on Geometry Processing. Nice, 11–21

  17. Weyrich T, Pauly M, Keiser R, Heinzle S, Scandella S, Gross M (2004) Post-processing of scanned 3D surface data. Proceedings of Eurographics Symposium on Point-Based Graphics. 85–94

  18. Schall O, Belyaev A, Seidel H (2005) Robust filtering of noisy scattered point data. Eurographics symposium on point-based graphics

  19. Shen J, Yoon D, Shehu D, Chang SY (2009) Spectral moving removal of non-isolated surface outlier clusters. Comput Aided Des 41(4):256–267

    Article  Google Scholar 

  20. Lloyd SP (1982) Least squares quantization in PCM. IEEE Trans Inf Theory 28(2):129–137

    Article  MathSciNet  MATH  Google Scholar 

  21. Wang Y, Feng HY (2015) Outlier detection for scanned point cloud using majority voting. Comput Aided Des 62(C):31–43

    Article  Google Scholar 

  22. Fabio R (2003) From point cloud to surface: the modeling and visualization problem. Int Arch Photogrammetry Rem Sens Spatial Inf Sci 34(5):W10

    Google Scholar 

  23. Ma J, Chen JS, Feng H, Wang L (2016) Automatic construction of watertight manifold triangle meshes from scanned point clouds using matched umbrella facets. Proceedings of 2016 CAD Conference and Exhibition. June 27–29, Vancouver, Canada, 1–6

  24. Digne J, Cohen-Steiner D, Alliez P, De Goes F, Desbrun M (2014) Feature-preserving surface reconstruction and simplification from defect-laden point sets. J Math Imaging Vision 48(2):369–382

    Article  MathSciNet  Google Scholar 

  25. Taubin GA (1995) Signal Processing approach to fair surface design. Proceedings of the 22nd Annual Conference on Computer Graphics and Interactive Techniques. August 6–11, Los Angeles, California, USA, 351–358

  26. Taubin G (2001) Linear anisotropic mesh filtering. Technical Report RC22213. IBM Research Division

  27. Vollmer J, Mencl R, Muller H (1999) Improved Laplacian smoothing of noisy surface meshes. Computer Graphics Forum 18(3):131–138

    Article  Google Scholar 

  28. Kobbelt L, Campagna S, Vorsatz J, Seidel H (1998) Interactive Multi-resolution Modeling on Arbitrary Meshes. Proceedings of the 25th Annual Conference on Computer Graphics and Interactive Techniques. July 19–24, Orlando, Florida, USA, 105–114

  29. Belyaev A, Ohtake Y (2003) A comparison of mesh smoothing methods. Israel-Korea Bi-National Conference on Geometric Modeling and Comput Graph. February 12–14, Tel-Aviv, Israel, 83–87

  30. Yagou H, Ohtake Y, Belyaev A (2002) Mesh smoothing via mean and median filtering applied to face normals. Geometric Modeling Processing. July 10–12, RIKEN, Saitama, Japan, 124–131

  31. Shen Y, Barner KE (2004) Fuzzy vector median-based surface smoothing. IEEE Trans Visual Comput Gr 10(3):266–277

    Article  Google Scholar 

  32. Yagou H, Ohtake Y, Belyaev A (2003) Mesh denoising via iterative alpha-trimming and non-linear diffusion of normals with automatic thresholding. Proceedings of Computer Graphics International 2003. July 9–11, Tokoyo, Japan, 28–33

  33. Ohtake Y, Belyaev A, Seidel H (2002) Mesh smoothing by adaptive and anisotropic Gaussian filter. Vision, modeling, and visualization 2002. November 20–22, Erlangen, 203–210

  34. Oliensis J (1993) Local reproducible smoothing without shrinkage. IEEE Trans Pattern Anal Mach Intell 15(3):307–312

    Article  Google Scholar 

  35. Peng J, Strela V, Zorin D (2001) A simple algorithm for surface denoising. IEEE Vis. October 21–26, San Diego, 107–112

  36. Alexa M (2002) Wiener filtering of meshes. Proceedings of Shape Modeling International. May 17–22, Banff, Alberta, Canada, 51–57

  37. Pauly M, Gross M (2001) Spectral processing of point-sampled geometry. Proceedings of the 25th Annual Conference on Computer Graphics and Interactive Techniques. August 12–17, Los Angeles, California, USA, 379–386

  38. Guskov I, Sweldens W, Schroder P (1999) Multiresolution signal processing for meshes. Proceedings of the 26th Annual Conference on Computer Graphics and Interactive Techniques. August 8–13, Los Angeles, California, USA, 325–334

  39. Schall O, Belyaev A, Seidel H (2007) Error-guided adaptive Fourier-based surface reconstruction. Comput Aided Des 39:421–426

    Article  Google Scholar 

  40. Kazhdan MM (2005) Reconstruction of solid models from oriented point sets. Proceedings of Symposium on Geometry Processing. 73–82

  41. Shen J, Maxim B, Akingbehin K (2005) Accurate correction of surface noises of polygonal meshes. Int J Numer Methods Eng 64(12):1678–1698

    Article  MATH  Google Scholar 

  42. Desbrun M, Meyer M, Schroder P, Barr AH (1999) Implicit fairing of irregular meshes using diffusion and curvature flow. Proceedings of the 26th Annual Conference on Computer Graphics and Interactive Techniques. August 8–13, Los Angeles, USA, 317–324

  43. Clarenz U, Diewald U, Rumpf M (2000) Anisotropic geometric diffusion in surface processing. Proceedings of IEEE Visualization. October 8–13, Salt Lake City, USA, 397–405

  44. Clarenz U, Rumpf M, Telea A (2004) Robust feature detection and local classification for surfaces based on moment analysis. IEEE Trans Visual Comput Gr 10(5):516–524

    Article  Google Scholar 

  45. Desbrun M, Meyer M, Schroder P, Barr AH (2000) Anisotropic feature-preserving denoising of height fields and bivariate data. Gr Interface. Montreal, 145–152

  46. Clarenz U, Dziuk G, Rumpf M (2003) On generalized mean curvature flow in surface processing. In: Karcher H, Hildebrandt S (eds) Springer, pp 217–248

  47. Sun Y, Page DL, Paik JK, Koschan A, Abidi MA (2002) Triangle mesh-based surface modeling using adaptive smoothing and implicit texture integration. Proceedings of First International Symposium on 3D Data Processing Visualization and Transmission. June 19–21, Padova, Italy, 588–597

  48. Schneider R, Kobbelt L (2000) Generating fair meshes with g1 boundary conditions. Proceedings of Geometric Modeling and Processing. April 10–12, Hong Kong, China, 251–261

  49. Whitaker RT (1998) A level-set approach to 3D reconstruction from range data. Int J Comput Vision 29(3):203–231

    Article  Google Scholar 

  50. Zhao HK, Osher S, Merriman B, Kang M (2000) Implicit and non-parametric shape reconstruction from unorganized points using variational level set method. Comput Vis Image Underst 80(3):295–314

    Article  MATH  Google Scholar 

  51. Gomes J, Faugeras OD (2000) Level sets and distance functions. Proceedings of Sixth European Conference on Computer Vision. June 26–July 1, Trinity College Dublin, Ireland, 588–602

  52. Cao F. Geometric curve evolution and image processing. Springer:2003

  53. Sapiro G, Tannenbaum A (1993) Affine invariant scale-space. Int J Comput Vision 11(1):25–44

    Article  MATH  Google Scholar 

  54. Moisan L (1998) Affine plane curve evolution: a fully consistent scheme. IEEE Trans Image Process 7(3):411–420

    Article  MathSciNet  MATH  Google Scholar 

  55. Lounsbery M, DeRose T, Warren J (1997) Multiresolution analysis for surfaces of arbitrary topological type. ACM Trans Gr 16(1):34–73

    Article  Google Scholar 

  56. Lee A, Moreton H, Hoppe H (2000) Displaced subdivision surfaces. Proceedings of the 27th Annual Conference on Computer Graphics and Interactive Techniques. July, New Orleans, Louisiana, USA, 85–94

  57. Razdan A, Mongkolnam P, Farin G (2003) Reverse engineering using a subdivision surface scheme. Proceedings of 8th 3D Modeling Symposium. April 23–24, Paris, France, 10

  58. Loop C (1987) Smooth subdivision surfaces based on triangles. M. Sc. The University of Utah

  59. Catmull E, Clark J (1978) Recursively generated B-spline surfaces on arbitrary topological meshes. Comput Aided Des 10(6):350–355

    Article  Google Scholar 

  60. Garland M, Heckbert PS (1997) Surface simplification using quadric error metrics. Proceedings of the 24th Annual Conference on Computer Graphics and Interactive Techniques. August 3–8, Los Angeles, California, USA, 209–216

  61. Kanai T (2001) MeshToSS: converting subdivision surfaces from dense meshes. Proceedings of the Vision Modeling and Visualization Conference 2001 (VMV-01). November 21–23, Stuttgart, Germany, 325–332

  62. Sadeghi J, Samavati FF (2011) Smooth reverse loop and Catmull-Clark subdivision. Graph Models 73(5):202–217

    Article  Google Scholar 

  63. Lancaster P, Salkauskas K (1981) Surfaces generated by moving least squares methods. Math Comput 37(155):141–158

    Article  MathSciNet  MATH  Google Scholar 

  64. Bentley JL (1990) K-d trees for semidynamic point sets. Proceedings of 6th Annual Symposium on Computational Geometry, 187–197

  65. Hoppe H, De Rose T, Duchamp T, MaDonald J, Stuetzle W (1993) Mesh optimization. ACM SIGGRAPH Comput Gr Proc 27:19–26

    Google Scholar 

  66. Press WH, Teukolsky SA, Vetterling WT, Flannery BP (1992) Numerical recipes in C: the art of scientific computing. Cambridge University Press, Cambridge

    MATH  Google Scholar 

  67. Beatson RK, Bui HQ (2003) Mollification formulas and implicit smoothing. Research Report UCDMS 2003/19. Dept. of Mathematics and Statistics, Univ. of Canterbury

  68. Carr JC, Beatson RK, McCallum BC, Fright WR, McLennan TJ, Mitchell TJ (2003) Smooth surface reconstruction from noisy range data. Proceedings of Graphite 2003. February 11–14, Melbourne, Australia, 119–126

  69. Ohtake Y, Belyaev A, Seidel H Multi-level partition of unity implicits. July 27–31, San Diego, 2003; 27–31

  70. Ohtake Y, Belyaev A, Seidel H (2004) 3D scattered data approximation with adaptive compactly supported radial basis functions. Proceedings of Shape Modeling International 2004. June 7–9, Genova, Italy, 31–39

  71. Savchenko VV, Pasko AA, Okunev OG, Kunii TL (1995) Function representation of solids reconstructed from scattered surface points and contours. Comput Gr Forum 14(4):181–188

    Article  Google Scholar 

  72. Turk G, O’Brien JF (1999) Variational implicit surfaces. Technical Report GIT-GVU-99–15. Georgia Institute of Technology

  73. Morse BS, Yoo TS, Rheingans P, Chen DT, Subramanian KR (2001) Interpolating implicit surfaces from scattered surface data using compactly supported radial basis functions. Proceedings of International Conference on Shape Modeling and pplications ‘01. May 7–11, Genova, Italy, IEEE Computer Society Press, 89–98

  74. Carr JC, Beatson RK, Cherrie JB, Mitchell TJ, Fright WR, McCallum BC, Evans TR (2001) Reconstruction and representation of 3D objects with radial basis functions. Proceedings of ACM SIGGRAPH. 67–76

  75. Perona P, Malik J (1990) Scale-space and edge detection using anisotropic diffusion. IEEE Trans Pattern Anal Mach Intell 12(7):629–639

    Article  Google Scholar 

  76. Meyer M, Desbrun M, Schroder P, Barr AH (2003) Discrete differential-geometry operators for triangulated 2-manifolds. In: visualization and mathematics III. Springer, Heidelberg, pp 35–57

    Chapter  Google Scholar 

  77. Zhang H, Fiume EL (2002) Mesh smoothing with shape or feature preservation. In: Vince J, Earnshaw R (eds) Advanced in modeling, animation, and rendering. Springer, pp 167–182

  78. Ohtake Y, Belyaev A, Bogaevski IA (2001) Mesh regularization and adaptive smoothing. Comput Aided Des 33(11):789–800

    Article  Google Scholar 

  79. Hildebrandt K, Polthier K (2004) Anisotropic filtering of non-linear surface features. Comput Gr Forum 23(3):391–400

    Article  Google Scholar 

  80. Tasdizen T, Whitaker RT, Burchard P, Osher S (2002) Anisotropic geometric diffusion in surface processing. IEEE Visualization. October 27–November 01, Boston, 2002; 125–132

  81. Bajaj C, Xu G (2003) Anisotropic diffusion of subdivision surfaces and functions on surfaces. ACM Trans Gr 22(1):4–32

    Article  Google Scholar 

  82. Loop C, DeRose T (1990) Generalized B-spline surfaces of arbitrary topology. Proceedings of the 17th Annual Conference on Computer Graphics and Interactive Techniques. August, Dallas, Texas, USA, 24(4):347–356

  83. Ma W, Kruth JP (1995) Parameterization of randomly measured points for least squares fitting of B-spline curves and surfaces. Comput Aided Des 27(9):663–675

    Article  MATH  Google Scholar 

  84. Eck M, Hoppe H (1996) Automatic reconstruction of B-spline surfaces of arbitrary topological type. Proceedings of the 23rd Annual Conference on Computer Graphics and Interactive Techniques. August 4–9ECK95, New Orleans, Louisiana, USA, 325–334

  85. Forsey DR, Bartels RH (1988) Hierarchical B-spline refinement. Proceedings of the 15th Annual Conference on Computer Graphics and Interactive Techniques. August 1–5, Atlanta, Georgia, USA, 22(4):205–212

  86. Forsey DR, Bartels RH (1995) Surface fitting with hierarchical splines. ACM Trans Gr 14(2):134–161

    Article  Google Scholar 

  87. Krishnamurthy V, Levoy M (1996) Fitting smooth surfaces to dense polygon meshes. Proceedings of the 23rd Annual Conference on Computer Graphics and Interactive Techniques. August 4–9, New Orleans, Louisiana, USA, 313–324

  88. Pfeifle R, Seidel H (1996) Fitting triangular B-splines to functional scattered data. Proceedings of Graphics Interface ‘95. May 17–19, Quebec, Quebec, Canada, 26–33

  89. Sarkar B, Menq CH (1991) Smooth-surface approximation and reverse engineering. Comput Aided Des 23(9):623–628

    Article  MATH  Google Scholar 

  90. Zhang C, Zhang P, Cheng F (2001) Fairing spline curves and surfaces by minimizing energy. Comput Aided Des 33(13):913–923

    Article  MATH  Google Scholar 

  91. Sapidis N, Farin G (1990) Automatic fairing algorithm for B-spline curves. Comput Aided Des 22(2):121–129

    Article  MATH  Google Scholar 

  92. Kjellander JAP (1983) Smoothing of bicubic parametric splines. Comput Aided Des 15(5):288–293

    Article  Google Scholar 

  93. Poliakoff JF, Wong YK, Thomas PD (1999) An automatic curve fairing algorithm for cubic B-spline curves. J Comput Appl Math 102(1):73–85

    Article  MathSciNet  MATH  Google Scholar 

  94. Jones TR, Durant F, Desbrun M (2003) Non-iterative, feature-preserving mesh smoothing. Proceedings of the 30th Annual Conference on Computer Graphics and Interactive Techniques. July 27–31, San Diego, California, USA, 943–949

  95. Fleishman S, Drori I, Cohen-Or D (2003) Bilateral mesh denoising. Proceedings of the 30th Annual Conference on Computer Graphics and Interactive Techniques. July 27–31, San Diego, California, USA, 950–953

  96. Tomasi C, Manduchi R (1998) Bilateral filtering for gray and color images. Proceedings of IEEE ICCV. January 4–7, Bombay, India, 836–846

  97. Choudhury P, Tumblin J (2003) The trilateral filter for high contrast images and meshes. Proceedings of the Eurographics Symposium on Rendering. Leuven, Belgium, 186–196

  98. Fleishman S, Cohen-Or D, Silva C (2005) Robust moving least-squares fitting with sharp features. ACM Trans Gr 24(3):544–552

    Article  Google Scholar 

  99. Wang J, Yu Z, Zhu W, Cao J (2013) Feature-preserving surface reconstruction from unoriented, noisy point data. Comput Gr Forum 32(1):164–176

    Article  Google Scholar 

  100. Reuter P, Joyot P, Trunzler J, Boubekeur T, Schlick C (2005) Surface reconstruction with enriched reproducing kernel particle approximation. Proceedings of the IEEE/Eurographics Symposium on Point-Based Graphics, 79–87

  101. Lipman Y, Cohen OR, Levin D (2007) Data-dependent MLS for faithful surface approximation. Proceedings of the Fifty Eurographics Symposium on Geometry Processing. 59–67

  102. Shi X, Shen J (2016) Genetic search for optimally-constrained multiple-line fitting of discrete data points. Appl Soft Comput 40(2):236–251

    Article  Google Scholar 

  103. Beyer HG (2001) The theory of evolutionary strategies. Heidelberg

  104. Goldberg DE, Korb B, Deb K (1989) Messy genetic algorithms: motivation, analysis, and first results. Complex Syst 3(5):493–530

    MathSciNet  MATH  Google Scholar 

  105. Holland JH (1975) Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence. U. Michigan Press, Ann Arbor

    MATH  Google Scholar 

  106. Beyer HG, Schwefel HP (2002) Evolution strategies—a comprehensive introduction. Nat Comput 1(1):3–52

    Article  MathSciNet  MATH  Google Scholar 

  107. Fogel DB (1994) An introduction to simulated evolutionary optimization. IEEE Trans Neural Networks 5(1):3–14

    Article  Google Scholar 

  108. Chellapilla K (1998) Combining mutation operators in evolutionary programming. IEEE Trans Evol Comput 2(3):91–96

    Article  Google Scholar 

  109. Yao X, Liu Y, Lin G (1999) Evolutionary programming made faster. IEEE Trans Evol Comput 3(2):82–102

    Article  Google Scholar 

  110. Kennedy J, Eberhart R (1995) Particle swarm optimization. Proceedings of IEEE International Conference on Neural Networks. Perth, WA, 4:1942–1948

  111. Daniels JI, Ha LK, Ochotta T, Silva CT (2007) Robust smooth feature extraction from point clouds. IEEE International Conference on Shape Modeling and Applications. 123–136

  112. Jenke P, Kruckeberg B, Straber W (2008) Surface reconstruction from fitted shape primitives. Proceedings of Vision Modeling and Visualization. 31–40

  113. Avron H, Sharf A, Greif C, Cohen-Or D (2010) L1-sparse reconstruction of sharp point set surfaces. ACM Trans Graphics 29(5):135-1–135-20

    Article  Google Scholar 

  114. Chen Y, Chen H, Shen J (2016) Fast voxel-based surface propagation method for outlier removal. 2016 CAD Conference and Exhibition. Vancouver, Canada, 1–5

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Acknowledgements

This article was supported in part by U.S. National Science Foundation DMI-0514900, CMMI-0721625, ECCS-1039563, and IIP-1445355.

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  1. School of Automotive Engineering, Shanghai University of Engineering Science, Shanghai, 201620, People’s Republic of China

    Hao Chen & Jie Shen

  2. Department of Computer and Information Science, University of Michigan-Dearborn, Dearborn, MI, 48128, USA

    Jie Shen

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  1. Hao Chen
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Chen, H., Shen, J. Denoising of point cloud data for computer-aided design, engineering, and manufacturing. Engineering with Computers 34, 523–541 (2018). https://doi.org/10.1007/s00366-017-0556-4

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