A Development Perspective of Point-Based Computer Graphics
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Published
Oct 30, 2021
Abstract
Every object has its characteristic shape, appearance and responses to physical interactions. Computer graphics center on those three components of an object to bring them onto the computer display. With the rapid development of three dimensional (3D) printing technology, the accuracy of the focused object’s geometry was put forward. Point-based graphing is a way to taking the role in rendering the huge 3D sampled data. Based on the digital geometry processing of point-sampled model, various algorithms were reviewed, and some related key techniques were compared with the potential perspective of the future work in this area was also presented．
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Keywords
Point-based computer graphics, Point-sampled model, Rendering, Point-based modeling
References
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18. Zeng Q, Qin Y, Chang W, Luo X. Correlating and evaluating the functionality-related properties with surface texture parameters and specific characteristics of machined components. Int J Mechan Sci 2018; 149:62-72. DOI: https://doi.org/10.1016/j.ijmecsci.2018.09.044
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22. Hu Q, Feng D, Zhang H, Yao Y, Aburaia M, Lammer H. Oriented to multi-branched structure unsupported 3D printing method research. Materials 2020; 13(9):2023. DOI: https://doi.org/10.3390/ma13092023
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24. Huang Z, Gong G, Han L, Song Z. Geometry surface simplication and reconstruction of FEM point cloud. 2010 International Conference on Computer Application and System Modeling (ICCASM 2010) 2010; pp.V5-357-V5-360. DOI: https://doi.org/10.1109/ICCASM.2010.5620131
25. Wu J, Kobbelt L. Optimized sub-sampling of point sets for surface splatting. Comput Graph Forum. 2004; 23:643-652. DOI: https://doi.org/10.1111/j.1467-8659.2004.00796.x
26. Taubin G. An improved algorithm for algebraic curve and surface fitting. 1993 (4th) International Conference on Computer Vision, 1993; pp.658-665. DOI: https://doi.org/10.1109/ICCV.1993.378149
27. Pereira A, Arruda M, Miranda A, Lira W, Martha L. Boolean operations on multi-region solids for mesh generation. Eng Comput 2012; 28:1-15. DOI: https://doi.org/10.1007/s00366-011-0228-8
28. Hu Y, Fang Y, Ge Z, Qu Z, Zhu Y, Pradhana A, Jiang C. A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Trans Graph 2018; 37:1-14. DOI: https://doi.org/10.1145/3197517.3201293
29. Biancolini ME, Chiappa A, Cella U, Costa E, Groth C, Porziani S. Radial basis functions mesh morphing. In: Krzhizhanovskaya V. et al. (eds) Computational Science – ICCS 2020. ICCS 2020. Lecture Notes in Computer Science, vol 12142. Springer, Cham. 2020. DOI: https://doi.org/10.1007/978-3-030-50433-5_23
30. Chen Y, Zhao J, Deng Q, Duan F. 3D craniofacial registration using thin-plate spline transform and cylindrical surface projection. PLoS One 2017; 12(10): e0185567. https://doi.org/10.1371/journal.pone.0185567
31. Keiser R, Adams B, Gasser D, Bazzi P, Dutre P, Gross M. A unified Lagrangian approach to solid-fluid animation. Proceedings Eurographics/IEEE VGTC Symposium Point-Based Graphics, 2005; pp.125-148, DOI: https://doi.org/10.1109/PBG.2005.194073
32. Pauly M, Keiser R, Adams B, Dutré P, Gross M, Guibas LJ. Meshless animation of fracturing solids. ACM Trans Graph 2005; 24(3):957-964. DOI: https://doi.org/10.1145/1186822.1073296
33. Yang P, Liu Y, Zhang X, Zhou X, Zhao Y. Simulation of fragmentation with material point method based on Gurson model and random failure. CMES - Comput Model Eng Sci 2012; 85: 207-237. DOI: https://doi.org/10.3970/cmes.2012.085.207
34. Simonsen BC, Li S. Mesh-free simulation of ductile fracture. Int J Num Meth Eng 2004; 60. 1425-1450. DOI: https://doi.org/10.1002/nme.1009
35. Xie M, Niu X. A 3D roaming and collision detection algorithm applicable for massive spatial data. PLoS One 2020; 15(2):e0229038. DOI: https://doi.org/10.1371/journal.pone.0229038
36. Akgunduz A, Banerjee P, Mehrotra S. A linear programming solution for exact collision detection. ASME J Comput Inf Sci Eng 2005; 5(1):48-55. DOI: https://doi.org/10.1115/1.1846053
37. Adams B, Ovsjanikov M, Wand M, Seidel HP, Guibas LJ. Meshless modeling of deformable shapes and their motion. Comput Animat 2008; 2008:77-86. DOI: https://doi.org/10.2312/SCA/SCA08/077-086
38. Wang S, Xiang N, Xia Y, You L, Zhang J. Real-time surface manipulation with C1 continuity through simple and efficient physics-based deformations. Vis Comput 2021; 37:2741-2753. DOI: https://doi.org/10.1007/s00371-021-02169-4
39. Hassanat ABA. Two-point-based binary search trees for accelerating big data classification using KNN. PLoS One 2018; 13(11):e0207772. DOI: https://doi.org/10.1371/journal.pone.0207772
40. Immonen E. A parametric morphing method for generating structured meshes for marine free surface flow applications with plane symmetry. Journal of Computational Design and Engineering 2019; 6(3):348-353. DOI: https://doi.org/10.1016/j.jcde.2018.11.002
41. Duan L, Luo X, Ruan L, Gu M. Novel method of boundary-free mesh parameterization. PLoS One 2019; 14(6):e0217537. DOI: https://doi.org/10.1371/journal.pone.0217537
42. Xiao C, Zheng W, Peng Q, Forrest A. (2004). Robust morphing of point-sampled geometry. J Vis Comput Animat 2004; 15:201-210. DOI: https://doi.org/10.1002/cav.22
43. Rusinkiewicz S, Levoy M. QSplat: A Multiresolution Point Rendering System for Large Meshes. Proceedings of SIGGRAPH 2001. DOI: https://doi.org/10.1145/344779.344940
44. Rusinkiewicz S, Levoy M. Streaming QSplat: A viewer for networked visualization of large, dense models. proceedings of the 2001 symposium on interactive 3D graphics, 2001. DOI: https://doi.org/10.1145/364338.364350
45. Srivastava DJ, Vosegaard T, Massiot D, Grandinetti PJ. Core Scientific Dataset Model: A lightweight and portable model and file format for multi-dimensional scientific data. PLoS One 2020; 15(1):e0225953. DOI: https://doi.org/10.1371/journal.pone.0225953
46. Wicke M, Teschner M, Gross M. CSG tree rendering for point-sampled objects. 12th Pacific Conference on Computer Graphics and Applications, 2004. PG 2004. Proceedings., 2004; pp.160-168, DOI: https://doi.org/10.1109/PCCGA.2004.1348346
47. Thalmann NM, Thalmann D. Transparency, texture, shadows, and anti-aliasing. In: Computer Animation. Computer Science Workbench. Springer, Tokyo. 1990. Print ISBN: 978-4-431-68107-6. DOI: https://doi.org/10.1007/978-4-431-68105-2_9
48. Zwicker M, Pfister H, Baar JV, Gross MH. Surface splatting. Proceedings of the 28th Annual Conference on Computer Graphics and Interactive techniques, 2001.
49. Botsch M, Kobbelt L. High-quality point-based rendering on modern GPUs. 2003; pp.335-343. DOI: https://doi.org/10.1109/PCCGA.2003.1238275
50. Pauly M, Keiser R, Kobbelt LP, Gross M. Shape modeling with point-sampled geometry. ACM Trans Graph 2003; 22(3):641-650. DOI: https://doi.org/10.1145/882262.882319
2. Yngve G, Turk G. Roust creation of implicit surfaces from polygonal meshes. Vis Comput Graph IEEE Transact 2002; 8:346-359. DOI: https://doi.org/10.1109/TVCG.2002.1044520
3. Chen Y, Medioni G. Object modelling by registration of multiple range images. Image Vision Comput 1992; 10(3):145-155. DOI: https://doi.org/10.1016/0262-8856(92)90066-C
4. Blais G, Levine MD. Registering multiview range data to create 3D computer objects. IEEE Trans Pattern Anal Mach Intell 1995; 17(8):820-824. DOI: https://doi.org/10.1109/34.400574
5. He Y, Liang B, Yang J, Li S, He J. An iterative closest points algorithm for registration of 3D laser scanner point clouds with geometric features. Sensors (Basel) 2017; 17(8):1862. DOI: https://doi.org/10.3390/s17081862
6. Alexa M, Behr J, Cohen-Or D, Fleishman S, Levin D, Silva CT. Computing and rendering point set surfaces. IEEE Trans Visual Comp Graph 2003; 9(1):3-15. DOI: https://doi.org/10.1109/TVCG.2003.1175093
7. Bacciaglia A, Ceruti A, Liverani A. Surface smoothing for topological optimized 3D models. Struct Multidisc Optim 2021; In press. DOI: https://doi.org/10.1007/s00158-021-03027-6
8. Fleishman S, Cohen-Or D, Silva CT. Robust moving least-squares fitting with sharp features. ACM Trans Graph 2005; 24:544-552. DOI: https://doi.org/10.1145/1186822.1073227
9. Jin Y, Jiang W, Shao J, Lu J. An improved image denoising model based on nonlocal means filter. Math Prob Eng 2018; 2018: 8593934. DOI: https://doi.org/10.1155/2018/8593934
10. Fan L, Zhang F, Fan H, Zhang C. Brief review of image denoising techniques. Vis Comput Ind Biomed Art 2019; 2:7. DOI: https://doi.org/10.1186/s42492-019-0016-7
11. Schall O, Belyaev A, Seidel HP. Adaptive feature-preserving non-local denoising of static and time-varying range data. Comput Aid Design 2008; 40(6):701-707. DOI: https://doi.org/10.1016/j.cad.2008.01.011
12. Buhmann MD. A new class of radial basis functions with compact support. Math Comput 2001; 70. DOI: https://doi.org/10.1090/S0025-5718-00-01251-5
13. Wang J, Oliveira M. Filling holes on locally smooth surfaces reconstructed from point clouds. Imag Vis Comput 2007; 25:103-113. DOI: https://doi.org/10.1016/j.imavis.2005.12.006
14. Park S, Guo X, Shin H, Qin H. Shape and appearance repair for incomplete point surfaces. Proceed IEEE Int Conf Comput Vis 2005; 2:1260-1267. DOI: https://doi.org/10.1109/ICCV.2005.218
15. Sharf A, Alexa M, Cohen-Or D. Context-based surface completion. ACM Trans Graph 2004; 23:878-887. DOI: https://doi.org/10.1145/1015706.1015814
16. Ji C, Li Y, Fan J, Lan S. A novel simplification method for 3D geometric point cloud based on the importance of point. IEEE Access 2019; pp.1-1. DOI: https://doi.org/10.1109/ACCESS.2019.2939684
17. Yang P, Qian X. Direct computing of surface curvatures for point-set surfaces. Eurographics Symposium on Point-Based Graphics 2007; pp.29-36. DOI: https://doi.org/10.2312/SPBG/SPBG07/029-036
18. Zeng Q, Qin Y, Chang W, Luo X. Correlating and evaluating the functionality-related properties with surface texture parameters and specific characteristics of machined components. Int J Mechan Sci 2018; 149:62-72. DOI: https://doi.org/10.1016/j.ijmecsci.2018.09.044
19. Kolluri R. Provably good moving least squares. ACM Trans Algor 2008; 4. DOI: https://doi.org/10.1145/1361192.1361195
20. Zhu L, Kukko A, Virtanen J-P, Hyypp J, Kaartinen H, Hyypp H, Turppa T. Multisource point clouds, point simplification and surface reconstruction. Remote Sens 2019; 11(22):2659. DOI: https://doi.org/10.3390/rs11222659
21. Du X, Yin B, Kong D. Adaptive out-of-core simplification of large point clouds. 2007 IEEE International Conference on Multimedia and Expo 2007; pp.1439-1442. DOI: https://doi.org/10.1109/ICME.2007.4284931
22. Hu Q, Feng D, Zhang H, Yao Y, Aburaia M, Lammer H. Oriented to multi-branched structure unsupported 3D printing method research. Materials 2020; 13(9):2023. DOI: https://doi.org/10.3390/ma13092023
23. Wang Y, Zheng J, Wang H. Fast mesh simplification method for three-dimensional geometric models with feature-preserving efficiency. Sci Program 2019; 2019:4926190. DOI: https://doi.org/10.1155/2019/4926190
24. Huang Z, Gong G, Han L, Song Z. Geometry surface simplication and reconstruction of FEM point cloud. 2010 International Conference on Computer Application and System Modeling (ICCASM 2010) 2010; pp.V5-357-V5-360. DOI: https://doi.org/10.1109/ICCASM.2010.5620131
25. Wu J, Kobbelt L. Optimized sub-sampling of point sets for surface splatting. Comput Graph Forum. 2004; 23:643-652. DOI: https://doi.org/10.1111/j.1467-8659.2004.00796.x
26. Taubin G. An improved algorithm for algebraic curve and surface fitting. 1993 (4th) International Conference on Computer Vision, 1993; pp.658-665. DOI: https://doi.org/10.1109/ICCV.1993.378149
27. Pereira A, Arruda M, Miranda A, Lira W, Martha L. Boolean operations on multi-region solids for mesh generation. Eng Comput 2012; 28:1-15. DOI: https://doi.org/10.1007/s00366-011-0228-8
28. Hu Y, Fang Y, Ge Z, Qu Z, Zhu Y, Pradhana A, Jiang C. A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Trans Graph 2018; 37:1-14. DOI: https://doi.org/10.1145/3197517.3201293
29. Biancolini ME, Chiappa A, Cella U, Costa E, Groth C, Porziani S. Radial basis functions mesh morphing. In: Krzhizhanovskaya V. et al. (eds) Computational Science – ICCS 2020. ICCS 2020. Lecture Notes in Computer Science, vol 12142. Springer, Cham. 2020. DOI: https://doi.org/10.1007/978-3-030-50433-5_23
30. Chen Y, Zhao J, Deng Q, Duan F. 3D craniofacial registration using thin-plate spline transform and cylindrical surface projection. PLoS One 2017; 12(10): e0185567. https://doi.org/10.1371/journal.pone.0185567
31. Keiser R, Adams B, Gasser D, Bazzi P, Dutre P, Gross M. A unified Lagrangian approach to solid-fluid animation. Proceedings Eurographics/IEEE VGTC Symposium Point-Based Graphics, 2005; pp.125-148, DOI: https://doi.org/10.1109/PBG.2005.194073
32. Pauly M, Keiser R, Adams B, Dutré P, Gross M, Guibas LJ. Meshless animation of fracturing solids. ACM Trans Graph 2005; 24(3):957-964. DOI: https://doi.org/10.1145/1186822.1073296
33. Yang P, Liu Y, Zhang X, Zhou X, Zhao Y. Simulation of fragmentation with material point method based on Gurson model and random failure. CMES - Comput Model Eng Sci 2012; 85: 207-237. DOI: https://doi.org/10.3970/cmes.2012.085.207
34. Simonsen BC, Li S. Mesh-free simulation of ductile fracture. Int J Num Meth Eng 2004; 60. 1425-1450. DOI: https://doi.org/10.1002/nme.1009
35. Xie M, Niu X. A 3D roaming and collision detection algorithm applicable for massive spatial data. PLoS One 2020; 15(2):e0229038. DOI: https://doi.org/10.1371/journal.pone.0229038
36. Akgunduz A, Banerjee P, Mehrotra S. A linear programming solution for exact collision detection. ASME J Comput Inf Sci Eng 2005; 5(1):48-55. DOI: https://doi.org/10.1115/1.1846053
37. Adams B, Ovsjanikov M, Wand M, Seidel HP, Guibas LJ. Meshless modeling of deformable shapes and their motion. Comput Animat 2008; 2008:77-86. DOI: https://doi.org/10.2312/SCA/SCA08/077-086
38. Wang S, Xiang N, Xia Y, You L, Zhang J. Real-time surface manipulation with C1 continuity through simple and efficient physics-based deformations. Vis Comput 2021; 37:2741-2753. DOI: https://doi.org/10.1007/s00371-021-02169-4
39. Hassanat ABA. Two-point-based binary search trees for accelerating big data classification using KNN. PLoS One 2018; 13(11):e0207772. DOI: https://doi.org/10.1371/journal.pone.0207772
40. Immonen E. A parametric morphing method for generating structured meshes for marine free surface flow applications with plane symmetry. Journal of Computational Design and Engineering 2019; 6(3):348-353. DOI: https://doi.org/10.1016/j.jcde.2018.11.002
41. Duan L, Luo X, Ruan L, Gu M. Novel method of boundary-free mesh parameterization. PLoS One 2019; 14(6):e0217537. DOI: https://doi.org/10.1371/journal.pone.0217537
42. Xiao C, Zheng W, Peng Q, Forrest A. (2004). Robust morphing of point-sampled geometry. J Vis Comput Animat 2004; 15:201-210. DOI: https://doi.org/10.1002/cav.22
43. Rusinkiewicz S, Levoy M. QSplat: A Multiresolution Point Rendering System for Large Meshes. Proceedings of SIGGRAPH 2001. DOI: https://doi.org/10.1145/344779.344940
44. Rusinkiewicz S, Levoy M. Streaming QSplat: A viewer for networked visualization of large, dense models. proceedings of the 2001 symposium on interactive 3D graphics, 2001. DOI: https://doi.org/10.1145/364338.364350
45. Srivastava DJ, Vosegaard T, Massiot D, Grandinetti PJ. Core Scientific Dataset Model: A lightweight and portable model and file format for multi-dimensional scientific data. PLoS One 2020; 15(1):e0225953. DOI: https://doi.org/10.1371/journal.pone.0225953
46. Wicke M, Teschner M, Gross M. CSG tree rendering for point-sampled objects. 12th Pacific Conference on Computer Graphics and Applications, 2004. PG 2004. Proceedings., 2004; pp.160-168, DOI: https://doi.org/10.1109/PCCGA.2004.1348346
47. Thalmann NM, Thalmann D. Transparency, texture, shadows, and anti-aliasing. In: Computer Animation. Computer Science Workbench. Springer, Tokyo. 1990. Print ISBN: 978-4-431-68107-6. DOI: https://doi.org/10.1007/978-4-431-68105-2_9
48. Zwicker M, Pfister H, Baar JV, Gross MH. Surface splatting. Proceedings of the 28th Annual Conference on Computer Graphics and Interactive techniques, 2001.
49. Botsch M, Kobbelt L. High-quality point-based rendering on modern GPUs. 2003; pp.335-343. DOI: https://doi.org/10.1109/PCCGA.2003.1238275
50. Pauly M, Keiser R, Kobbelt LP, Gross M. Shape modeling with point-sampled geometry. ACM Trans Graph 2003; 22(3):641-650. DOI: https://doi.org/10.1145/882262.882319
How to Cite
Mukti, A. (2021). A Development Perspective of Point-Based Computer Graphics. Science Insights, 39(2), 343–352. https://doi.org/10.15354/si.21.re231
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