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Surface Area Estimation Using 3D Point Clouds and Delaunay Triangulation

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Proceedings of the Second International Conference on Innovations in Computing Research (ICR’23)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 721))

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Abstract

Estimating the surface area of a stockpile is a crucial challenge in several fields, including in construction projects. While modern remote sensing platforms are increasingly popular, their utility in indoor stockpiles is limited, and their use in outdoor settings can be cost-prohibitive. This study presents a straightforward and cost-effective approach for estimating the surface area of both indoor and outdoor stockpiles using 3D point cloud data and the Delaunay triangulation technique. A mobile phone camera is used to capture a video of the stockpile, from which a 3D point cloud is generated, followed by the production of a mesh to reconstruct its surface via Delaunay triangulation. The proposed method’s output is the stockpile’s surface area, which is estimated by summing the surfaces of individual triangles. Experimental results from a laboratory setting on small-scale stockpiles indicate that this method is an effective approach to measuring stockpile surface areas and has the potential for widespread use in various stockpiles in different settings.

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References

  1. Putra, C.A., Syaifullah, J.S.W., et al.: Approximate volume of sand materials stockpile based on structure from motion (SFM). In: 2020 6th Information Technology International Seminar (ITIS), pp. 135–139. IEEE (2020)

    Google Scholar 

  2. Sălăgean, T., Șuba, E.E., Pop, I.D., Matei, F., Deak, J.: Determining stockpile volumes using photogrammetric methods. Scientific papers. Series e. land reclamation, earth observation & surveying. Environ. Eng. 8, 114–119 (2019)

    Google Scholar 

  3. Mora, O.E., et al.: Accuracy of stockpile estimates using low-cost SUAS photogrammetry. Int. J. Remote Sens. 41(12), 4512–4529 (2020)

    Google Scholar 

  4. Mackenzie, D.D., Naeth, M.A.: Native seed, soil and atmosphere respond to boreal forest topsoil (LFH) storage. PLoS ONE 14(9), e0220367 (2019)

    Google Scholar 

  5. Yang, X., Huang, Y., Zhang, Q.: Automatic stockpile extraction and measurement using 3D point cloud and multi-scale directional curvature. Remote Sens. 12(6), 960 (2020)

    Article  Google Scholar 

  6. Shishido,H., Wanzhi, Z., Jang, H., Kawamura, Y., Kameda, Y., Kitahara, I.: Clustering method of 3D point cloud of muck-pile based on connectivity of adjacent surface. In: 2019 IEEE 8th Global Conference on Consumer Electronics (GCCE), pp. 770–774. IEEE (2019)

    Google Scholar 

  7. Farhood, H., Perry, S., Cheng, E., Kim, J.: Enhanced 3D point cloud from a light field image. Remote Sens. 12(7), 1125 (2020)

    Article  Google Scholar 

  8. Yongbing, X., Liu, K., Ni, J., Li, Q.: 3D reconstruction method based on second-order semiglobal stereo matching and fast point positioning delaunay triangulation. PLoS ONE 17(1), e0260466 (2022)

    Article  Google Scholar 

  9. Delaunay, B., Spherevide, S.: A la memoire de georges voronoi. Bulletin de l’Académie des Sciences de l’URSS, Classe des Sciences Mathématiques et Naturelles 6, 793–800 (1934)

    Google Scholar 

  10. Agisoft. https://www.agisoft.com/. Jan 2023

  11. Arango, C., Morales, C.A.: Comparison between multicopter UAV and total station for estimating stockpile volumes. Int. Arch. Photogram. Remote Sens. Spat. Inf. Sci. 40(1), 131 (2015)

    Article  Google Scholar 

  12. Kavanagh, B.F., Bird, S.J., et al.: Surveying: principles and applications (1984)

    Google Scholar 

  13. Annich, A., El Abderrahmani, A., Satori, K.: Fast and easy 3D reconstruction with the help of geometric constraints and genetic algorithms. 3D Res. 8, 1–21 (2017)

    Google Scholar 

  14. Jiang, Y., et al.: Automatic volume calculation and mapping of construction and demolition debris using drones, deep learning, and GIS. Drones 6(10), 279 (2022)

    Article  Google Scholar 

  15. Tamin, M.A., Darwin, N., Majid, Z., Ariff, M.F.M., Idris, K.M., et al.: Volume estimation of stockpile using unmanned aerial vehicle. In: 2019 9th IEEE International Conference on Control System, Computing and Engineering (ICCSCE), pp. 49–54. IEEE (2019)

    Google Scholar 

  16. Lu, T.-F., Zhao, S., Xu, S., Koch, B., Hurdsman, A.: A 3D of system for3 dimensional stockpile surface scanning using laser. In: 2011 6th IEEE Conference on Industrial Electronics and Applications, pp. 1–5. IEEE (2011)

    Google Scholar 

  17. Jia-Chong, D., Teng, H.-C.: 3D laser scanning and GPS technology for landslide earthwork volume estimation. Autom. Constr. 16(5), 657–663 (2007)

    Article  Google Scholar 

  18. Ashtiani, M.Z., Muench, S.T., Gent, D., Uhlmeyer, J.S.: Application of satellite imagery in estimating stockpiled reclaimed asphalt pavement (rap) inventory: a Washington state case study. Constr. Build. Mater. 217, 292–300 (2019)

    Google Scholar 

  19. Carrera-Hernandez, J.J., Levresse, G., Lacan, P.: Is UAV-SFM surveying ready to replace traditional surveying techniques? Int. J. Remote Sens. 41(12), 4820–4837 (2020)

    Article  Google Scholar 

  20. Shalaby, A., Elmogy, M., El-Fetouh, A.A.: Algorithms and applications of structure from motion (SFM): a survey. Algorithms 6(06) (2017)

    Google Scholar 

  21. Opencv-VideoCapture. https://docs.opencv.org/3.4/d8/dfe/classcv11VideoCapture.html. Accessed Feb 2023

  22. Opencv library imwrite. https://docs.opencv.org/3.4/d4/da8/groupimgcodecs.html#gabbc7ef1aa2edfaa87772f1202d67e0ce. Accessed Feb 2023

  23. Opencv-Denoising. https://docs.opencv.org/3.4/d1/d79/groupphotodenoise.html. Accessed Jan 2023

  24. Liu, Y., Zheng, Y.: Accurate volume calculation driven by Delaunay triangulation for coal measurement. Sci. Program. 1–10 (2021)

    Google Scholar 

  25. Jose-Llorens. Stockpile volume with Open3D. https://jose-llorens-ripolles.medium.com/stockpile-volume-with-open3d-fa9d32099b6f/. Accessed Feb 2023

  26. Delaunay. https://docs.scipy.org/doc/scipy/reference/generated/scipy.spatial.Delaunay.html. Accessed Jan 2023

  27. Yusheng, X., Tong, X., Stilla, U.: Voxel-based representation of 3D point clouds: methods, applications, and its potential use in the construction industry. Autom. Constr. 126, 103675 (2021)

    Article  Google Scholar 

  28. Open3d surface area. http://www.open3d.org/docs/release/pythonapi/open3d.geometry.TriangleMesh.html. Accessed Feb 2023

  29. Kazhdan, M., Bolitho, M., Hoppe, H.: Poisson surface reconstruction. In: Proceedings of the Fourth Eurographics Symposium on Geometry Processing, vol. 7 (2006)

    Google Scholar 

  30. Open3D Poisson surface reconstruction. http://www.open3d.org/docs/latest/tutorial/Advanced/surfacereconstruction.html#Poisson-surface-reconstruction. Accessed Feb 2023

  31. Xu, X., Jiang, M.: 3D meteorological radar data visualization with point cloud completion and Poissonsurface reconstruction. In: Yu, S. et al. (eds.) PRCV 2022. LNCS, vol. 13536, pp. 137–150. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-18913-5_11

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Author information

Authors and Affiliations

  1. School of Mathematical and Physical Sciences, Macquarie University, Sydney, Australia

    Helia Farhood & Samuel Muller

  2. School of Mathematics and Statistics, University of Sydney, Sydney, Australia

    Samuel Muller

  3. School of Computing, Macquarie University, Sydney, Australia

    Helia Farhood & Amin Beheshti

Authors
  1. Helia Farhood
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  2. Samuel Muller
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  3. Amin Beheshti
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Corresponding author

Correspondence to Helia Farhood .

Editor information

Editors and Affiliations

  1. University of Detroit Mercy, Farmington Hills, MI, USA

    Kevin Daimi

  2. Asia Pacific International College, Sydney, NSW, Australia

    Abeer Al Sadoon

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Farhood, H., Muller, S., Beheshti, A. (2023). Surface Area Estimation Using 3D Point Clouds and Delaunay Triangulation. In: Daimi, K., Al Sadoon, A. (eds) Proceedings of the Second International Conference on Innovations in Computing Research (ICR’23). Lecture Notes in Networks and Systems, vol 721. Springer, Cham. https://doi.org/10.1007/978-3-031-35308-6_3

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