An Innovative Approach of Evaluating the Accuracy of Point Cloud Generated by Photogrammetry-Based 3D Reconstruction
Publication: Computing in Civil Engineering 2021
ABSTRACT
The theoretical accuracy of photogrammetry-based reconstruction has been studied intensively in literature, but the problem remains in evaluating the accuracy of the generated point cloud in real practice. Typically, checking the coordinates of ground control points (GCPs) using total station is considered a promising approach. However, the GCPs are artificial objects with clear and identifiable features and have consistent normal vectors or less roughness than natural objects, which cannot be considered as typical samples to evaluate the point cloud accuracy. Therefore, the present paper proposes an innovative method based on cloud-to-cloud comparison to evaluate the accuracy of point clouds generated from the SfM-MVS algorithm. The proposed method utilizes close-range photogrammetry with high accuracy as the referencing point cloud. A case study is carried out on a piece of the bare soil surface, which is about 1,000 m2 with about a 1.5 m elevation variance. Compared to the GCPs-based method, the proposed method is more reliable in evaluating the accuracy of the 3D point cloud model.
Get full access to this chapter
View all available purchase options and get full access to this chapter.
REFERENCES
Barazzetti, L. (2017). “Network design in close-range photogrammetry with short baseline images.” Proc., 26th International CIPA Symposium on Digital Workflows for Heritage Conservation 2017, Copernicus GmbH, 17–23.
Furukawa, Y., Curless, B., Seitz, S. M., and Szeliski, R. (2010). “Towards Internet-scale Multi-view Stereo.” 2010 Ieee Conference on Computer Vision and Pattern Recognition, Ieee Computer Soc, Los Alamitos, 1434–1441.
Furukawa, Y., and Ponce, J. (2010). “Accurate, Dense, and Robust Multiview Stereopsis.” Ieee Transactions on Pattern Analysis and Machine Intelligence, 32(8), 1362–1376.https://doi.org/10.1109/tpami.2009.161.
Green, S., Bevan, A., and Shapland, M. (2014). “A comparative assessment of structure from motion methods for archaeological research.” Journal of Archaeological Science, 46, 173–181.https://doi.org/10.1016/j.jas.2014.02.030.
Harwin, S., and Lucieer, A. (2012). “Assessing the Accuracy of Georeferenced Point Clouds Produced via Multi-View Stereopsis from Unmanned Aerial Vehicle (UAV) Imagery.” Remote Sensing, 4(6), 1573–1599.https://doi.org/10.3390/rs4061573.
James, M. R., Robson, S., and Smith, M. W. (2017). “3-D uncertainty-based topographic change detection with structure-from-motion photogrammetry: precision maps for ground control and directly georeferenced surveys.” Earth Surface Processes and Landforms, 42(12), 1769–1788.https://doi.org/10.1002/esp.4125.
Luhmann, T. (2010). “Close range photogrammetry for industrial applications.” ISPRS Journal of Photogrammetry and Remote Sensing, 65(6), 558–569.https://doi.org/10.1016/j.isprsjprs.2010.06.003.
Luhmann, T., Fraser, C., and Maas, H. G. (2016). “Sensor modelling and camera calibration for close-range photogrammetry.” Isprs Journal of Photogrammetry and Remote Sensing, 115, 37–46.https://doi.org/10.1016/j.isprsjprs.2015.10.006.
Luhmann, T., Robson, S., Kyle, S., and Boehm, J. (2014). Close-Range Photogrammetry and 3-D Imaging, 2nd edition, De Gruyter, Berlin, Germany, 683 pp.
Martinez-Carricondo, P., Aguera-Vega, F., Carvajal-Ramirez, F., Mesas-Carrascosa, F. J., Garcia-Ferrer, A., and Perez-Porras, F. J. (2018). “Assessment of UAV-photogrammetric mapping accuracy based on variation of ground control points.” Int. J. Appl. Earth Obs. Geoinf., 72, 1–10.https://doi.org/10.1016/j.jag.2018.05.015.
Rieke-Zapp, D., Tecklenburg, W., Peipe, J., Hastedt, H., and Haig, C. (2009). “Evaluation of the geometric stability and the accuracy potential of digital cameras — Comparing mechanical stabilisation versus parameterisation.” ISPRS Journal of Photogrammetry and Remote Sensing, 64(3), 248–258.https://doi.org/10.1016/j.isprsjprs.2008.09.010.
Sapirstein, P. 2016. “Accurate measurement with photogrammetry at large sites.” Journal of Archaeological Science, 66, 137–145.https://doi.org/10.1016/j.jas.2016.01.002.
Smith, M. W., Carrivick, J. L., and Quincey, D. J. (2016). “Structure from motion photogrammetry in physical geography.” Prog. Phys. Geogr., 40(2), 247–275.https://doi.org/10.1177/0309133315615805.
Tavani, S., Pignalosa, A., Corradetti, A., Mercuri, M., Smeraglia, L., Riccardi, U., Seers, T., Pavlis, T., and Billi, A. (2020). “Photogrammetric 3D Model via Smartphone GNSS Sensor: Workflow, Error Estimate, and Best Practices.” Remote Sensing, 12(21).https://doi.org/10.3390/rs12213616.
Tonkin, T. N., and Midgley, N. G. (2016). “Ground-Control Networks for Image Based Surface Reconstruction: An Investigation of Optimum Survey Designs Using UAV Derived Imagery and Structure-from-Motion Photogrammetry.” Remote Sensing, 8(9), 8.https://doi.org/10.3390/rs8090786.
Information & Authors
Information
Published In
Computing in Civil Engineering 2021
Pages: 926 - 933
History
Published online: May 24, 2022
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.