* Corresponding Author
Comparative Assessment on the Use of Videogrammetry and Photogrammetry for Rapid and Low-Cost Three-Dimensional Modeling
https://doi.org/10.22146/ijg.87960 Muhammad Ulin Nuha(1*), Alif Farhan Pramudya(2), Bonifasius Efraim Laia(3), Rainaldy Husain(4), Danang Setiaji(5), Een Lujainatul Isnaini(6), Redho Surya Perdana(7), Aulia Try Atmojo(8), Retnadi Heru Jatmiko(9)
(1) Remote Sensing and Photogrammetry Research Group, Geomatics Engineering, Institut Teknologi Sumatera, Lampung, 35365, Indonesia
(2) Student at Geomatics Engineering, Institut Teknologi Sumatera, Lampung, 35365, Indonesia
(3) Student at Geomatics Engineering, Institut Teknologi Sumatera, Lampung, 35365, Indonesia
(4) Student at Geomatics Engineering, Institut Teknologi Sumatera, Lampung, 35365, Indonesia
(5) Mapping Surveyor at Indonesian Geospatial Information Authority, Bogor, 16911, Indonesia
(6) Geodesy, Hydrography, and Surveying Research Group, Geomatics Engineering, Institut Teknologi Sumatera, Lampung, 35365, Indonesia
(7) Geodesy, Hydrography, and Surveying Research Group, Geomatics Engineering, Institut Teknologi Sumatera, Lampung, 35365, Indonesia
(8) Geodesy, Hydrography, and Surveying Research Group, Geomatics Engineering, Institut Teknologi Sumatera, Lampung, 35365, Indonesia
(9) Study Program of Cartography and Remote Sensing, Department of Geographic Information Science, Faculty of Geography, Universitas Gadjah Mada, Yogyakarta, 55281, Indonesia
(*) Corresponding Author
Abstract
The current activities in photogrammetry technology such as the permission to apply non-metric cameras, development of Structure from Motion (SfM), and potential usage of videogrammetry are part of the answers to the need for low-cost camera-based mapping. Therefore, this study aimed to test and compare the accuracy of photogrammetry and videogrammetry methods for three-dimensional (3D) modeling obtained using a non-metric camera with SfM processing. Terrestrial Laser Scanner (TLS) was used to obtain comparative data and the results showed a degradation of photo resolution in videogrammetry method, causing a reduction in the number of point clouds produced compared to photogrammetry. Moreover, the point cloud test showed that the surface variation results for both methods were identical to 3D modeling with a higher point density recorded in photogrammetry and the relative distance was different by 0.125 meters. The average difference in point cloud between photogrammetry and TLS was 0.062 meters while videogrammetry and TLS had 0.106 meters. The absolute test produced an RMSE value of 0.022 meters for photogrammetry and 0.032 meters for videogrammetry at a 95% confidence interval, indicating the two methods produced similar data quality. The results led to the conclusion that videogrammetry had satisfactory values and could be used as an alternative in 3D modeling but was not considered better than photogrammetry.
Received: 2023-08-13 Revised: 2024-05-27 Accepted: 2024-09-20 Published: 2024-10-10
Keywords
References
Abdullah, S., Tahar, K. N., Fadzil, M., Rashid, A., Osoman, M. A., Services, G., & Bhd, S. (2019). Camera Calibration Performance on Different Non-metric Cameras. Pertanika Journal of Science and Technology, 27(3), 1397–1406. http://www.pertanika.upm.edu.my/
Agüera-Vega, F., Martínez-Carricondo, P., & Carvajal-Ramírez, F. (2023). Enhancing Uav-Sfm 3D Models Accuracy of Unique Heritage Infrastructures. Case of Isabel Ii Dam, Almeria, Spain. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLVIII-M-2–2023, 51–57. https://doi.org/10.5194/isprs-archives-xlviii-m-2-2023-51-2023
Ahmad, N., Azri, S., Ujang, U., Cuétara, M. G., Retortillo, G. M., & Mohd Salleh, S. (2019). Comparative Analysis of Various Camera Input for Videogrammetry. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 42(4/W16), 63–70. https://doi.org/10.5194/isprs-archives-XLII-4-W16-63-2019
Al Khalil, O. (2020). Structure from Motion (SfM) Photogrammetry as Alternative to Laser Scanning for 3D Modelling of Historical Monuments. Open Science Journal. https://doi.org/10.23954/osj.v5i2.2327
Deliry, S. I., & Avdan, U. (2023). Accuracy evaluation of UAS photogrammetry and structure from motion in 3D modeling and volumetric calculations. Journal of Applied Remote Sensing, 17(02). https://doi.org/10.1117/1.jrs.17.024515
Elkhrachy, I. (2021). Accuracy Assessment of Low-Cost Unmanned Aerial Vehicle (UAV) Photogrammetry. Alexandria Engineering Journal, 60(6), 5579–5590. https://doi.org/10.1016/j.aej.2021.04.011
Eltner, A., & Sofia, G. (2020). Structure from motion photogrammetric technique. In Developments in Earth Surface Processes (Vol. 23, pp. 1–24). Elsevier B.V. https://doi.org/10.1016/B978-0-444-64177-9.00001-1
Fabris, M., Fontana Granotto, P., & Monego, M. (2023). Expeditious Low-Cost SfM Photogrammetry and a TLS Survey for the Structural Analysis of Illasi Castle (Italy). Drones, 7(2). https://doi.org/10.3390/drones7020101
Herráez, J., Martínez, J. C., Coll, E., Martín, M. T., & Rodríguez, J. (2016). 3D modeling by means of videogrammetry and laser scanners for reverse engineering. Measurement: Journal of the International Measurement Confederation, 87, 216–227. https://doi.org/10.1016/j.measurement.2016.03.005
Iheaturu, C. J., Ayodele, E. G., & Okolie, C. J. (2020). An Assessment of The Accuracy of Structure-From-Motion (Sfm) Photogrammetry For 3D Terrain Mapping. Geomatics, Landmanagement and Landscape, 2, 65–82. https://doi.org/10.15576/GLL/2020.2.65
Ishida, K. (2017). Investigating the accuracy of 3D models created using SfM. 34th International Symposium on Automation and Robotics in Construction. https://doi.org/10.22260/ISARC2017/0117
Javadnejad, F., Slocum, R. K., Gillins, D. T., Olsen, M. J., & Parrish, C. E. (2021). Dense Point Cloud Quality Factor as Proxy for Accuracy Assessment of Image-Based 3D Reconstruction. Journal of Surveying Engineering, 147(1). https://doi.org/10.1061/(asce)su.1943-5428.0000333
Jia, C. C., Wang, C. J., Yang, T., Fan, B. H., & He, F. G. (2018). A 3D Point Cloud Filtering Algorithm based on Surface Variation Factor Classification. Procedia Computer Science, 154, 54–61. https://doi.org/10.1016/j.procs.2019.06.010
Kaiser, T., Clemen, C., & Block-Berlitz, M. (2022). Co-Registration Of Video-Grammetric Point Clouds With Bim - First Conceptual Results. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 46(5/W1-2022), 141–148. https://doi.org/10.5194/isprs-archives-XLVI-5-W1-2022-141-2022
Kovanič, Ľ., Peťovský, P., Topitzer, B., & Blišťan, P. (2024). Spatial Analysis of Point Clouds Obtained by SfM Photogrammetry and the TLS Method—Study in Quarry Environment. Land, 13(5), 614. https://doi.org/10.3390/land13050614
Kurniawan, R. A., Ramdani, F., & Furqon, M. T. (2017). Videogrammetry: A new approach of 3-dimensional reconstruction from video using SfM algorithm: Case study: Coal mining area. International Symposium on Geoinformatics. https://doi.org/10.1109/ISYG.2017.8280665
Murtiyoso, A., & Grussenmeyer, P. (2021). Experiments using smartphone-based videogrammetry for low-cost cultural heritage documentation. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. https://doi.org/10.5194/isprs-archives-XLVI-M-1-2021-487-2021ï
Murtiyoso, A., Grussenmeyer, P., & Freville, T. (2017). Close range uav accurate recording and modeling of St-Pierre-Le-Jeune Neo-Romanesque church in Strasbourg (France). International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 42(2W3), 519–526. https://doi.org/10.5194/isprs-archives-XLII-2-W3-519-2017
Murtiyoso, A., Koehl, M., Grussenmeyer, P., & Freville, T. (2017). Acquisition And Processing Protocols For Uav Images: 3D Modeling of Historical Buildings Using Photogrammetry. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 4(2W2), 163–170. https://doi.org/10.5194/isprs-annals-IV-2-W2-163-2017
Ortiz-Coder, P., & Sánchez-Ríos, A. (2020). An integrated solution for 3D heritage modeling based on videogrammetry and V-SLAM technology. Remote Sensing, 12(9). https://doi.org/10.3390/RS12091529
Parente, L., Chandler, J. H., & Dixon, N. (2019). Optimising the quality of an SfM-MVS slope monitoring system using fixed cameras. Photogrammetric Record, 34(168), 408–427. https://doi.org/10.1111/phor.12288
Peña-Villasenín, S., Gil-Docampo, M., & Ortiz-Sanz, J. (2019). Professional SfM and TLS vs a simple SfM photogrammetry for 3D modelling of rock art and radiance scaling shading in engraving detection. Journal of Cultural Heritage, 37, 238–246. https://doi.org/10.1016/j.culher.2018.10.009
Pepe, M., Alfio, V. S., Costantino, D., & Herban, S. (2022). Rapid and Accurate Production of 3D Point Cloud via Latest-Generation Sensors in the Field of Cultural Heritage: A Comparison between SLAM and Spherical Videogrammetry. Heritage, 5(3), 1910–1928. https://doi.org/10.3390/heritage5030099
Ramirez, D., Jayasuriya, S., & Spanias, A. (2022). Towards Live 3D Reconstruction from Wearable Video: An Evaluation of V-SLAM, NeRF, and Videogrammetry Techniques. Interservice/Industry Training, Simulation, and Education Conference. https://doi.org/10.48550/arXiv.2211.11836
Rogova, N. (2020). Application of non-metric digital cameras to control the volume of soil displaced when performing earthworks. E3S Web of Conferences, 164. https://doi.org/10.1051/e3sconf/202016402025
Rokhmana, C. A., Tjahjadi, M. A., & Agustina, F. D. (2019). Cadastral Surveys with Non-metric Camera Using Uav: A Feasibility Study. KnE Engineering. https://doi.org/10.18502/keg.v4i3.5856
S Sai, S., Tjahjadi, M. E., & A Rokhmana, C. (2019). Geometric Accuracy Assessments of Orthophoto Production from UAV Aerial Images. KnE Engineering. https://doi.org/10.18502/keg.v4i3.5876
Saif, W., & Alshibani, A. (2022). Smartphone-Based Photogrammetry Assessment in Comparison with a Compact Camera for Construction Management Applications. Applied Sciences (Switzerland), 12(3). https://doi.org/10.3390/app12031053
Siong, E. H. H., Ariff, M. F. M., & Razali, A. F. (2023). The Application of Smartphone Based Structure from Motion (SFM) Photogrammetry in Ground Volume Measurement. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 48(4/W6-2022), 145–152. https://doi.org/10.5194/isprs-archives-XLVIII-4-W6-2022-145-2023
Sobura, S. (2021). Calibration of non-metric uav camera using different test fields. Geodesy and Cartography (Vilnius), 47(3), 111–117. https://doi.org/10.3846/gac.2021.13080
Torresani, A., & Remondino, F. (2019). Videogrammetry vs Photogrammetry for Heritage 3D Reconstruction. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 42(2/W15), 1157–1162. https://doi.org/10.5194/isprs-archives-XLII-2-W15-1157-2019
Zhang, H., Aldana-Jague, E., Ois Clapuyt, F., Wilken, F., Vanacker, V., & Oost, K. Van. (2019). Evaluating the Potential of PPK Direct Georeferencing for UAV-SfM Photogrammetry and Precise Topographic Mapping. Earth Surface Dynamics. https://doi.org/10.5194/esurf-2019-2
DOI: https://doi.org/10.22146/ijg.87960
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