Examining the degree of stability of the internal parameters camera of smartphones in the videogrammetric method to calculate the volume of earthworks

Shafiei, Mehran; Milan, Asghar

doi:10.61186/jgst.14.3.89

[Home ] [Archive]

[ فارسی ]

Journal of Geomatics Science and Technology

Main Menu

Home

Browse

Journal Info

Guide for Authors

Submit Manuscript

Articles archive

For Reviewers

Contact us

Site Facilities

Reviewers

Search in website

Receive site information

Volume 14, Issue 3 (3-2025)

JGST 2025, 14(3): 89-113

Back to browse issues page

Examining the degree of stability of the internal parameters camera of smartphones in the videogrammetric method to calculate the volume of earthworks

Mehran Shafiei

, Asghar Milan ^*

Abstract: (252 Views)

Nowadays, with the advancement of technology, the enhancement of computers computational power, and the availability of user-friendly software, there is a trend towards replacing inexpensive tools such as smartphones with expensive and specialized equipment for 3D modeling increased. Therefore, these tools must be evaluated based on scientific criteria. For this reason, in this study, the capabilities of smartphone cameras as data collection tools have been examined. To examine the stability of internal orientation parameters, firstly the cameras of ten smartphones were calibrated three times over fourteen days using a chessboard pattern and Vertical lines. The results showed continuous changes in their internal parameter values. To investigate whether the instability is caused by the weakness of the calibration method, the imaging geometry, or the structure of the smartphone camera, the most stable item was selected and re-calibrated twice in a row, and then its results were used. The proposed process was implemented on two concrete samples with a regular shape and one sand sample with an irregular shape on a small scale, whose volumes were precisely determined in advance by laboratory methods. The volume of the samples was estimated with the videogrammetry method and implementation of pre-calibration and self-calibration. The effect of pre-calibration and self-calibration methods on the accuracy of volume estimation in the laboratory scale was very insignificant. The results showed differences from a minimum of 1.28% to a maximum of 2.98% with the actual volumes. In the final investigation, the study was conducted on a workshop-scale sand depot with approximate dimensions of 3.50_Hx11_Wx16_L meters. The number of twenty ground points around the feature was defined using coded targets and the coordinates of their were taken by Total-station. To verify the accuracy of the measurements, a target rod with a known length was obliquely placed on the sand depot. The volume of the sand depot was also determined by surveying using a Total station, and it was used as the basis for comparing the accuracy of the videogrammetry method. The measurement error of the target rod length on the two models produced in the pre-calibration and self-calibration modes was determined to be 8 and 3 mm, respectively. In both modes, models with uniform distribution and high density of points were obtained, which had a difference of 5.8% and 1% relative to the volume, respectively estimated by the Total-station method.

Article number: 7

Keywords: Self-calibration, smartphone, Structure from Motion, pre-calibration, 3D model

Full-Text [PDF 1343 kb] (112 Downloads)

Type of Study: Research | Subject: Photo&RS
Received: 2024/07/5

References

1. Fawzy., H. E. (2015). "The accuracy of determining the volumes using close range photogrammetry." IOSR Journal of Mechanical and Civil Engineering, 12(2), 10-15.

2. Wang, X., Al-Shabbani, Z., Sturgill, R., Kirk, A., & Dadi, G. B. (2017). "Estimating earthwork volumes through use of unmanned aerial systems." Transportation Research Record, 2630(1), 1-8. [DOI:10.3141/2630-01]

3. Hugenholtz, C. H., Walker, J., Brown, O., & Myshak, S. (2015). "Earthwork volumetrics with an unmanned aerial vehicle and softcopy photogrammetry." Journal of Surveying Engineering, 141(1), 06014003. [DOI:10.1061/(ASCE)SU.1943-5428.0000138]

4. Asri, N. A., & Ahmad, A. (2012). "The use of digital image for volume determination using digital close range photogrammetric method." In 2012 IEEE 8th International Colloquium on Signal Processing and its Applications (pp. 321-324). IEEE. [DOI:10.1109/CSPA.2012.6194742]

5. Vladan Blahni, Schindelbeck. (2021). "Smartphone imaging technology and its applications." From the journal Advanced Optical Technologies . https://doi.org/10.1515/aot-2021-0023 [DOI:1515/10/aot-2021-0023]

6. DXO, Smartphones versus Cameras: Closing the Gap on Image Quality. (2020). Available at: https://www.dxomark.com/smartphones-vs-cameras-closing-the-gap-on-image-quality/.

7. Smith MW, Carrivick JL and Quincey DJ. (2016). "Structure from motion photogrammetry in physical geography." Progress in Physical Geography 40(2): 247-275 [DOI:10.1177/0309133315615805]

8. Ouédraogo MM, Degré A, Debouche C and Lisein J. (2014). "The evaluation of unmanned aerial system-based photogrammetry and terrestrial laser scanning to generate DEMs of agricultural watersheds." Geomorphology 214: 339-355. [DOI:10.1016/j.geomorph.2014.02.016]

9. Fonstad MA, Dietrich JT, Courville BC, Jensen JL and Carbonneau PE. (2013). "Topographic structure from motion: a new development in photogrammetric measurement." Earth Surface Processes and Landforms 38(4): 421-430. [DOI:10.1002/esp.3366]

10. OpenCV. Open-Source Computer Vision Library. (2015). Available online: https://opencv.org (accessed on 14 December 2022).

11. Open Drone Map [Computer Software]. (2017). Available online: https://opendronemap.org (accessed on 14 December 2022).

12. Meshroom is a free, open-source 3D Reconstruction Software based on the AliceVision Photogrammetric Computer Vision framework. (2018).Availableonline https://github.com/alicevision/Meshroom (accessed on 14 December 2022).

13. Agisoft Cloud is an online platform for site inspection, annotation and documentation integrated with cloud processing service for the Metashape Professional users. https://www.agisoft.com/.2023 Agisoft

14. Applications of Photogrammetry and PhotoModeler. https://www.photomodeler.com/.2023.

15. Matuzeviˇcius, D.; Serackis, A. (2021). "Three-Dimensional Human Head Reconstruction Using Smartphone-Based Close-Range Video Photogrammetry." Appl. Sci. 2021, 12, 229. [DOI:10.3390/app12010229]

16. M.J. Westoby, J. Brasington, N.F. Glasser, M.J. Hambrey, J.M. Reynolds. (2012). "Structure-from-Motion' photogrammetry: A low-cost, effective tool for geoscience applications." [DOI:10.1016/j.geomorph.2012.08.021]

17. N. Michelettia, J. H. Chandlerb, S. N. Lanea. (2014). " Investigating the geomorphological potential of freely available and accessible Structure-from-Motion photogrammetry using a smartphone." Earth Surface processes and landform [DOI:10.1002/esp.3648]

18. Li X. (1999). "Photogrammetric Investigation into Low-Resolution Digital Camera Systems." Department of Geodesy and Geomatics Engineering, University of New Brunswick

19. Triggs B. (1998). "Autocalibration from planar scenes." European Conference on Computer Vision ECCV98: 89-105. [DOI:10.1007/BFb0055661]

20. Zhang Z. (2000). "A flexible new technique for camera calibration." IEEE Transactions on Pattern Analysis and Machine Intelligence 22(11): 1330-1334. [DOI:10.1109/34.888718]

21. Fraser CS. (2013). "Automatic camera calibration in close range photogrammetry." Photogrammetric Engineering & Remote Sensing 79(4): 381-388 [DOI:10.14358/PERS.79.4.381]

22. Clarke T.A, Fryer J.G. (1998). "The development of camera calibration methods and models." The Photogrammetric Record, 16 (91) (1998), 51-66 [DOI:10.1111/0031-868X.00113]

23. Rongfu Tang. (2013). "Mathematical Methods for Camera Self-Calibration in Photogrammetry and Computer Vision." Faculty of Aerospace Engineering and Geodesy of the Universität Stuttgart

24. DXO, Disruptive Technologies: Mobile Imaging taking Smartphone Cameras to Next Level, 2018a. Available at: https://www.dxomark.com/disruptive-technologies-mobile-imaging-taking-smartphone-cameras-next-level/

25. Apollonio, F.; Fantini, F., Garagnani, S., Gaiani, M. (2021). "A Photogrammetry-Based Workflow for the Accurate 3D Construction and Visualization of Museums Assets." Remote Sens. 13, 486. [DOI:10.3390/rs13030486]

26. Gaiani, M., Apollonio, F.I., Fantini, F. (2019). "Evaluating Smartphones Color Fidelity and Metric Accuracy for the 3d Documentation of Small Artifacts." ISPRS-Int. Arch. Photogramm. Remote. Sens. Spat. Inf. Sci. XLII-2/W11, 539-547. [DOI:10.5194/isprs-archives-XLII-2-W11-539-2019]

27. Brandolini, F., Cremaschi, M., Zerboni, A., Degli Esposti, M., Mariani, G.S., Lischi, S. (2020). "SFM-photogrammetry for fast recording of archaeological features in remote areas."

28. Brandolini F. et al. (2019). "Estimating the potential of archaeo-historical data in the definition of geomorphosites and geo-educational itineraries in the Central Po Plain (N Italy)." Geoheritage, 11, 1371-1396. [DOI:10.1007/s12371-019-00382-1]

29. Ali Asadpour. (2021). "Documenting historic tileworks using smartphone-based photogrammetry." Mersin Photogrammetry Journal -3(1); 15-20 [DOI:10.53093/mephoj.899432]

30. Beltrami C. et al. (2019). "3D digital and physical reconstruction of a collapsed dome using SFM techniques from historical images." The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 42-2/W11, 217-224. [DOI:10.5194/isprs-archives-XLII-2-W11-217-2019]

31. G. Vacca, A. Dessi. (2022). "Geomatic supporting knowledge of cultural heritage aimed at recovery and restoration. The International Archives of the Photogrammetry." Remote Sensing and Spatial Information Sciences [DOI:10.5194/isprs-archives-XLIII-B2-2022-909-2022]

32. L. H. Hansen, T. M. Pedersen, E. Kjems, S. Wyke. (2021). "Smartphone-based reality capture for subsurface utilities: experiences from water utility companies in Denmark." The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences

33. K. N. Fauzan, D. Suwardhi, A. Murtiyoso, I. Gumilar, T. P. Sidiq. (2021). "Close-range photogrammetry method for SF6 Gas Insulated Line (GIK) deformation monitoring." The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences,

34. Abdul Hannan Qureshi, Wesam Salah Alaloul, Arnadi Murtiyoso, Syed Saad, Bilal Manzoor. (2022). "Comparison of photogrammetry tools considering rebar progress recognition." The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences.

35. Kirim Lee, Won Hee Lee. (2022). "Earthwork Volume Calculation, 3D Model Generation, and Comparative Evaluation Using Vertical and High-Oblique Images Acquired by Unmanned Aerial Vehicles." Aerospace [DOI:10.3390/aerospace9100606]

36. Young Hyun Kim, Seung Su Shin, Hyun Kyu Lee, Eun Soo Park. (2022). "Field Applicability of Earthwork Volume Calculations Using Unmanned Aerial Vehicle." Sustainability ,14, 9331 [DOI:10.3390/su14159331]

37. Abbas zadeh, Saeid. (2018). "Evaluation of Close-range photogrammetry capability in comparison with land mapping in order to calculate the volume of earthworks." Technical Faculties, Mapping Engineering Department Tehran university.

38. Karami, A., sousouni, B., Hosseininaveh, A. (2015). "A novel contactless approach for calculating volumes of objects." The 1st National Conference on Geospatial Information Technology

39. Rafał Wróżyński, Krzysztof Pyszny, Mariusz Sojka, Czesław Przybyła, and Sadżide Murat-Błażejewska. (2017). "Ground volume assessment using 'Structure from Motion' photogrammetry with a smartphone and a compact camera." Open Geosci.; DOI 1515/10/geo-2017-0023 [DOI:10.1515/geo-2017-0023]

40. Hossam El-Din Fawzy. (2018). "Study the accuracy of digital close range photogrammetry technique software as a measuring tool." Alexandria Engineering Journal 58, 171-179. [DOI:10.1016/j.aej.2018.04.004]

41. Wahib Saif and Adel Alshibani. (2022). "Smartphone-Based Photogrammetry Assessment in Comparison with a Compact Camera for Construction Management Applications." Appl. Sci. 12, 1053. https://doi.org/ 3390/10/app12031053 https://doi.org/10.3390/app12031053 [DOI:3390/10/app12031053]

42. Elvis Ha Heng Siong, Mohd Farid Mohd Ariff, Ahmad Firdaus Razali. (2022). "The application of smartphone based structure from motion (sfm) photogrammetry in ground volume measurement." The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLVIII-4/W6 [DOI:10.5194/isprs-archives-XLVIII-4-W6-2022-145-2023]

43. Wahib Saif, Adel Alshibani.2023. A Close-Range Photogrammetric Model for Tracking and Performance Based Forecasting Earthmoving Operat.https://www.researchgate.net/publication/371446255 [DOI:10.1108/CI-12-2022-0323]

44. Bessin, Z., Jaud, M., Letortu, P., Vassilakis, E., Evelpidou, N., Costa, S., Delacourt, C., 2023. Smartphone Structure-from-Motion Photogrammetry from a Boat for Coastal Cliff Face Monitoring Compared with Pléiades Tri-Stereoscopic Imagery and Unmanned Aerial System Imagery. Remote Sensing, 15(15): 3824. [DOI:10.3390/rs15153824]

45. Patonis, P. (2024). A Comparative Study on the Use of Smartphone Cameras in Photogrammetry Applications. Sensors 2024, 24, 7311. https://doi.org/10.3390/s24227311 [DOI:10.3390/s24227311.]

46. Wolf, P. R., DeWitt, B. A., & Wilkinson, B. E. (2014). Elements of photogrammetry with applications in GIS (4th ed.). New York, NY: McGraw-Hill Education.

47. Z. Zhang. (2004). "Camera calibration with one-dimensional objects." IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 26, no. 7, pp. 892-899. [DOI:10.1109/TPAMI.2004.21]

48. Tsai, R. Y. (1987). A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses. IEEE Journal of Robotics and Automation, 3(4), 323-344. [DOI:10.1109/JRA.1987.1087109]

49. Ferruh Yilmazturk, Ali Ersin Gurbak. (2019). "Geometric Evaluation of Mobile-Phone Camera Images for 3D Informatio." Hindawi International Journal of Optics Volume, Article ID 8561380, 10 pages [DOI:10.1155/2019/8561380]

50. Fryer J.G, Brown D.C. (1986). "Lens distortion for close-range photogrammetry." Photogrammetric Engineering & Remote Sensing. 51-58.

51. Rostam. Gol mohammadei. (2016). "Guide to measuring and evaluating lighting in the work environment." Student publications. Hamedan

52. B. Triggs, P. F. McLauchlan, R. I. Hartley, and A. W. Fitzgibbon. (1999). "Bundle adjustment-a modern synthesis, in International workshop on vision algorithms." pp. 298-372: Springer [DOI:10.1007/3-540-44480-7_21]

Send email to the article author

Add your comments about this article

‎ 10.61186/jgst.14.3.89

Mendeley

Zotero

RefWorks

Shafiei M, Milan A. Examining the degree of stability of the internal parameters camera of smartphones in the videogrammetric method to calculate the volume of earthworks. JGST 2025; 14 (3) : 7
URL: http://jgst.issgeac.ir/article-1-1192-en.html

Rights and permissions
	This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Volume 14, Issue 3 (3-2025)

Back to browse issues page