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Tytuł artykułu

The Impact of Photo Overlap, the Number of Control Points and the Method of Camera Calibration on the Accuracy of 3D Model Reconstruction

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This research attempted to determine the optimal photo overlap, number of control points and method of camera calibration for a photogrammetric 3D model reconstruction of an object of cultural heritage value. Terrestrial images of the object were taken with a hand held digital camera and processed in the ContextCapture software using the Structure from Motion (SfM) algorithm. A total station was used to measure ground control points (GCPs) and check points. Here, the research workflow, methodology, and various analyses concerning different configurations of the aforementioned factors are described. An at tempt to assess the parameters which should be implemented in order to pro vide a high degree of accuracy of the model and reduce time consumption both during fieldwork and data processing was taken. The manuscript discusses the results of the analyses and compares them with other studies presented by different authors and indicates further potential directions of studies within this scope. Based on the authors’ experience with this research, some general conclusions and remarks concerning the planning of photo acquisition from the terrestrial level for the purpose of 3D model reconstruction were formulated.
Rocznik
Strony
67--87
Opis fizyczny
Bibliogr. 35 poz., fot., rys., tab., wykr.
Twórcy
autor
  • AGH University of Science and Technology, Faculty of Mining Surveying and Environmental Engineering, Krakow, Poland
  • AGH University of Science and Technology, Faculty of Mining Surveying and Environmental Engineering, Krakow, Poland
Bibliografia
  • [1] Hellman T., Lahti M.: Photogrammetric 3D modeling for virtual reality. 2018. https://www.researchgate.net/publication/327227913 [access: 28.11.2020].
  • [2] Oats R.C., Escobar‑Wolf R., Oommen T.: A novel application of photogrammetry for retaining wall assessment. Infrastructures, vol. 2, no. 3, 2017, pp. 1–12. https://doi.org/10.3390/infrastructures2030010.
  • [3] Roncella R., Re C., Forlani G.: Performance Evaluation of a Structure and Motion Strategy in Architecture and Cultural Heritage. ISPRS – International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XXXVIII-5, March 2012, pp. 285–292. https://doi.org/10.5194/isprsarchives-xxxviii-5-w16-285-2011.
  • [4] Green S.: A Comparative Assessment of Structure from Motion Methods for Archaeological Research. Journal of Archaeological Science, vol. 46, June 2014, pp. 173–181. https://doi.org/10.1016/j.jas.2014.02.030.
  • [5] Samaan M., Deseilligny M.P., Heno R., De La Vaissière E., RogerJ.: Close-range photogrammetric tools for epigraphic surveys. Journal on Computing and Cultural Heritage, vol. 9, no. 3, 2016, pp. 1–18. https://doi.org/10.1145/2966985.
  • [6] Cignetti M., Godone D., Wrzesniak A., Giordan D.: Structure from Motion Multisource Application for Landslide Characterization and Monitoring: The Champlas du Col Case Study, Sestriere, North‑Western Italy. Sensors (Switzerland), vol. 19, no. 10, 2019, art. no. 2364. https://doi.org/10.3390/s19102364.
  • [7] Medjkane M., Maquaire O., Costa S., Roulland Th., Letortu P., Fauchard C., Antoine R., Davidson R.: High‑resolution monitoring of complex coastal morphology changes: cross‑efficiency of SfM and TLS-based survey (Vaches‑Noirescliffs, Normandy, France). Landslides, vol. 15, no. 6, 2018, pp. 1097–1108. https://doi.org/10.1007/s10346-017-0942-4.
  • [8] Verma A.K., Bourke M.C.: A method based on structure‑from‑motion photogrammetry to generate sub‑millimetre‑resolution digital elevation models for investigating rock breakdown features. Earth Surface Dynamics, vol. 7, no. 1, 2019, pp. 45–66. https://doi.org/10.5194/esurf-7-45-2019.
  • [9] Widya A.R., Monno Y., Imahori K., Okutomi M., Suzuki S., Gotoda T., Miki K.: 3D Reconstruction of Whole Stomach from Endoscope Video Using Structure‑from‑Motion. [in:] 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE, Berlin, Germany, 2019, pp. 3900–3904. https://doi.org/10.1109/EMBC.2019.8857964.
  • [10] Hussien D.A., Abed F.M., Hasan A.A.: Stereo photogrammetry vs computed tomography for 3D medical measurements. Karbala International Journal of Modern Science, vol. 5, no. 4, 2019, pp. 201–212. https://doi.org/10.33640/2405-609X.1130.
  • [11] Chiabrando F., Donadio E., Rinaudo F.: SfM for orthophoto generation: A winning approach for cultural heritage knowledge. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences – ISPRS Archives, vol. XL-5/W7, 2015, pp. 91–98. https://doi.org/10.5194/isprsarchives-XL-5-W7-91-2015.
  • [12] Lewińska P., Pargieła K.: Comparative Analysis of Structure-From-Motion Software’s – An Example of Letychiv (Ukraine) Castle and Convent Buildings. Journal of Applied Engineering Sciences, vol. 8, no. 2, 2019, pp. 73–78. https://doi.org/10.2478/jaes-2018-0021.
  • [13] Brandolini F., Patrucco G.: Structure‑from‑Motion (SFM) Photogrammetry as a Non‑Invasive Methodology to Digitalize Historical Documents: A Highly Flexible and Low‑Cost Approach? Heritage, vol. 2, no. 3, 2019, pp. 2124–2136. https://doi.org/10.3390/heritage2030128.
  • [14] Sergeeva A.D., Sablina V.A.: Using structure from motion for monument 3D reconstruction from images with heterogeneous background. [in:] 2018 7th Mediterranean Conference on Embedded Computing (MECO), IEEE, Budva, Montenegro, 2018, pp. 1–4. https://doi.org/10.1109/MECO.2018.8406058.
  • [15] Bekele M.K., Pierdicca R., Frontoni E., Malinverni E.S., Gain J.: A survey of augmented, virtual, and mixed reality for cultural heritage. Journal on Computing and Cultural Heritage, vol. 11, no. 2, 2018, art. no. 7. https://doi.org/10.1145/3145534.
  • [16] Miles H.C., Wilson A., Labrosse F. et al.: Alternative representations of 3D­-reconstructed heritage data. Journal on Computing and Cultural Heritage, vol. 9, no. 1, 2015, art. no. 4. https://doi.org/10.1145/2795233.
  • [17] ContextCapture. Quick guide for photo acquisition. Bentley, 2016.
  • [18] Agisoft Metashape User Manual. Agisoft LLC, 2019.
  • [19] Micheletti N., Chandler J.H., Lane S.N.: Structure from Motion (SfM) Photogrammetry. Geomorphological Techniques, vol. 2, sec. 2.2, 2015, pp. 1–12.
  • [20] Kwiatek K., Tokarczyk R.: Immersive photogrammetry in 3D modelling. Geomatics and Environmental Engineering, vol. 9, no. 2, 2015, pp. 51–62. https://doi.org/10.7494/geom.2015.9.2.51.
  • [21] Westoby M.J., Brasington J., Glasser N.F., Hambrey M.J., Reynolds J.M.: ‘Structure‑from‑Motion’ photogrammetry: A low‑cost, effective tool for geoscience applications. Geomorphology, vol. 179, December 2012, pp. 300–314. https://doi.org/10.1016/j.geomorph.2012.08.021.
  • [22] Verhoeven G.J.J.: Taking computer vision aloft – Archaeological three‑dimensional reconstructions from aerial photographs with PhotoScan. Archaeological Prospection, vol. 18(1), 2011, pp. 67–73.
  • [23] Shah Y., Raut S., Wadle S., Patil S.: A Study of Structure from Motion Photogrammetry for Generating 3D Model from 2D Images. IOSR Journal of Engineering, vol. 4, 2018, pp. 72–76.
  • [24] Nyimbili P.H., Demirel H., Seker D.Z., Erden T.: Structure from Motion (SfM) – Approaches and Applications. [in:] Spatial Data Processing, Modelling, Analysing and Management for Knowledge Based Systems, International Scientific Conference on Applied Sciences, 27–30 September 2016 – Antalya, Turkey, 2016.
  • [25] PHOTOMOD 6.2 User manual Processing of UAS data.
  • [26] Zomrawi N., Hussien M.A., Mohamed H.: Accuracy evaluation of digital aerial triangulation. International Journal of Engineering and Innovative Technology, vol. 2, no. 10, 2013, pp. 7–11.
  • [27] Khoshelham K.: Role of tie points in integrated sensor orientation for photogrammetric map compilation. Photogrammetric Engineering and Remote Sensing, vol. 75, no. 3, 2009, pp. 305–311. https://doi.org/10.14358/PERS.75.3.305.
  • [28] Harwin S., Lucieer A., Osborn J.: The impact of the calibration method on the accuracy of point clouds derived using unmanned aerial vehicle multi‑view stereopsis. Remote Sensing, vol. 7, no. 9, 2015, pp. 11933–11953. https://doi.org/10.3390/rs70911933.
  • [29] Oniga E., Breaban A.I., Florian S.: Determining the Optimum Number of Ground Control Points for Obtaining Determining the optimum number of ground control points for obtaining high precision results based on UAS images. Proceedings, vol. 2, no. 7, 2018, art. no. 352. https://doi.org/10.3390/ecrs‑2-05165.
  • [30] Sanz‑Ablanedo E., Chandler J.H., Rodríguez‑Pérez J.R., Ordóñez C.: Accuracy of Unmanned Aerial Vehicle (UAV) and SfM photogrammetry survey as a function of the number and location of ground control points used. Remote Sensing, vol. 10, no. 10, 2018, art. no. 1606. https://doi.org/10.3390/rs10101606.
  • [31] Villanueva J.K.S., Blanco A.C.: Optimization of Ground Control Point (GCP) Configuration for Unmanned Aerial Vehicle (UAV) Survey Using Structure from Motion (SFM). International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XLII-4/W12, 2019, pp. 167–174.
  • [32] Torres‑Sánchez J., López‑Granados F., Borra‑Serrano I., Manuel Peña J.: Assessing UAV-collected image overlap influence on computation time and digital surface model accuracy in olive orchards. Precision Agriculture, vol. 19, no. 1, 2018, pp. 115–133. https://doi.org/10.1007/s11119-017-9502-0.
  • [33] Czarnecka D.: Z Krakowa do Kirowa. O pomniku Iwana Koniewa w latach 1987–1991. Res Gestae. Czasopismo Historyczne, vol. 12, 2012, pp. 204–226.
  • [34] Stachnik P.: Koniew w Krakowie. Ani miasta nie ocalił, ani na cokole długo nie postał. Nasza Historia, 29.12.2016. https://naszahistoria.pl/koniew-w-krakowieani-miasta-nie-ocalil-ani-na-cokole-dlugo-nie-postal/ar/11659862 [access: 20.05.2020].
  • [35] PI-Calib. Operation Manual Camera Calibration Software. TOPCON. http://www.terrageomatics.com/downloads/PI-calib-manual.pdf [access: 28.11.2020].
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e860fe2d-8d84-4929-bcce-aab71fc4f580
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