This paper intends to point out the possibility of using Internet photogrammetry to construct 3D models from the images obtained by means of UAVs (Unmanned Aerial Vehicles). The solutions may be useful for the inspection of ports as to the content of cargo, transport safety or the assessment of the technical infrastructure of port and quays. The solution can be a complement to measurements made by using laser scanning and traditional surveying methods. In this paper the authors recommend a solution useful for creating 3D models from images acquired by the UAV using non-metric images from digital cameras. The developed algorithms, created and presented software allows to generate 3D models through the Internet in two modes: anaglyph and display in shutter systems. The problem of 3D image generation in photogrammetry is solved by using epipolar images. The appropriate method was presented by Kreiling in 1976. However, it applies to photogrammetric images for which the internal orientation is known. In the case of digital images obtained with non-metric cameras it is required to use another solution based on the fundamental matrix concept, introduced by Luong in 1992. In order to determine the matrix which defines the relationship between left and right digital image it is required to have at least eight homologous points. To determine the solution it is necessary to use the SVD (singular value decomposition). By using the fundamental matrix the epipolar lines are determined, which makes the correct orientation of images making stereo pairs, possible. The appropriate mathematical bases and illustrations are included in the publication.
If the inline PDF is not rendering correctly, you can download the PDF file here.
1. Bielewicz E. Gorski J.: Shells with random geometric imperfections simulation - based approach. International Journal of Non-Linear Mechanics 2002 Vol. 37 Iss. 4-5 pp.777-784 DOI: 10.1016/S0020-7462(01)00098-1
2. Burdziakowski P. Szulwic J.: A commercial of the shelf components for an unmanned air vehicle photogrammetry. 16th International Multidisciplinary Scientific GeoConference SGEM 2016 www.sgem.org SGEM2016 Conference Proceedings ISBN 978-619-7105-59-9 / ISSN 1314-2704 June 28 - July 6 2016 Book 2 Vol. 2 pp. 739-746 DOI: 10.5593/SGEM2016/B22/S10.095
3. Cho W. Schenk T. & Madanim M.: Resampling Digital Imagery to Epipolar Geometry. Proceedings of XVIIth ISPRS Congress Technical Commission III: Mathematical Analysis of Data Washington D.C. USA ISPRS Archives 1992 Volume XXiX Part B3 pp. 404-408.
4. Eisenbeiss H.: UAV photogrammetry. Diss. ETH No.18515 Institute of Geodesy and Photogrammetry Zurich Switzerland Mitteilungen 2009 No.105. p. 235.
5. Elias R.: Projective Geometry for Three-Dimensional Computer Vision. Multiple View Geometry in Computer Vision. Proceedings of Seventh World Multi-conference on Systemics Cybernetics and Informatics SCI’03. Orlando USA 2003 Vol. V pp. 99-104.
6. Förstner W.: New orientation procedures. The International Archives of Photogrammetry and Remote Sensing 2000 Vol. XXXIII-B3A pp. 297-304.
7. Górski J. Mikulski T. Oziębło M. Winkelmann K.: Effect of geometric imperfections on aluminium silo capacities. Stahlbau 2015 Vol. 84 iss. 1 pp.52-57
8. Hartley R. Zisserman A.: Multiple View Geometry in Computer Vision. Cambridge University Press Cambridge UK 2000.
9. Hartley R.I.: In defense of the eight-point algorithm. IEEE Transactions on Pattern Analysis and Machine Intelligence 1997 Vol. 19 Iss. 6 pp. 580-593.
10. Janowski A. Nagrodzka-Godycka K. Szulwic J. Ziolkowski P.: Remote sensing and photogrammetry techniques in diagnostics of concrete structures. Computers and Concrete 2016 Vol. 18 Iss. 3 pp. 405-420 DOI: 10.12989/cac.2016.18.3.405
11. Janowski A. Nowak A. et al.: Mobile Indicators in GIS and GPS Positioning Accuracy in Cities. Lecture Notes in Computer Science 2014 Vol. 8537 pp. 309-318 DOI: 10.1007/978-3-319-08729-0_31
12. Kaliński K. J. Buchholz C.: HILS for the design of threewheeled mobile platform motion surveillance system with a use of energy performance index. Solid State Phenomena 2013 Vol. 198 pp. 90-95.
13. Kaliński K. Mazur M.: Optimal control of 2-wheeled mobile robot at energy performance index. Mechanical Systems and Signal Processing 2016 Vol. 70-71 pp. 373-386.
14. Kozak J. Tarelko W.: Case study of masts damage of the sail training vessel Pogoria. Engineering Failure Analysis. 2011 Vol. 18 Iss. 3 pp. 819-827
15. Litwin W.: Water lubricated marine stern tube bearings - attempt at estimating hydrodynamic capacity. ASME/STLE 19-21.10.2009 Proceedings of the ASME/ STLE International Joint Tribology Conference 2010. DOI: 10.1115/IJTC2009-15068
16. Longuet-Higgins H.: A computer algorithm for reconstructing a scene from two projections. Nature 1982 Vol. 293 pp. 133-135.
17. Luczak M. Manzato S. Peeters B. Branner K. Berring P. Kahsin M.: Updating finite element model of a wind turbine blade section using experimental modal analysis results. Shock and Vibration Vol. 2014 iss. 1 pp.71-82
18. Luong Q.T.: Fundamental matrix and self-calibration. PhD Thesis University of Paris Orsay 1992.
19. Luong Q.T. Faugeras O.D.: The fundamental matrix: Theory algorithms and stability analysis. International Journal of Computer Vision 1996 Vol. 17 Iss. 1 pp. 43-75 DOI: 10.1007/BF00127818.
20. McGlone J.C. Mikhail E.M Bethel J. & Mullen R.: Manual of Photogrammetry. Fifth edition. American Society for Photogrammetry and Remote Sensing Maryland USA 2004.
21. Nejadasl F.K. Lindenbergh R.: Sequential and automatic image-sequence registration of road areas monitored from a hovering helicopter. Sensors 2014 Vol. 14 Iss. 9 pp. 16630-16650 DOI:10.3390/s140916630.
22. Paszotta Z. Szulwic J. Szumilo M.: Internet photogrammetry as a tool for e-learning. 8th International Conference of Education Research and Innovation 2015 ICERI2015 ISBN: 978-84-608-2657-6 pp. 4565-4573
23. Paszotta Z. Szumilo M.: A web-based approach for online digital terrain model and orthoimage generation. International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences 2010 Vol. 38-4 Iss. W13 WebMGS 2010: 1st International Workshop on Pervasive Web Mapping Geoprocessing and Services Como Italy 2010.08.26-27 ISSN 2194-9034.
24. Press W. Flannery B. Teukolsky S. & Vetterling W.: Numerical recipes in C: The Art of Scientific Computing. 2nd ed. pp. 59-70 Cambridge University Press UK. 1992.
25. Przyborski M. Szczechowski B. Szubiak W. Szulwic J. & Widerski T.: Photogrammetric development of the threshold water at the dam on the Vistula river in Wloclawek from unmanned aerial vehicles (UAV). 15th International Multidisciplinary Scientific Geoconference SGEM 2015 Albena Bulgaria June 18-24 2015. DOI: 10.5593/SGEM2015/B31/S12.063
26. Ruzgienė B. Aksamitauskas C. Daugėla I. Prokopimas S. Puodžiukas V. & Rekus D.: UAV photogrammetry for road surface modeling. The Baltic Journal of Road and Bridge Engineering Vilnius Technika 2015 Vol X No. 2 p. 151-158 DOI: 10.3846/bjrbe.2015.19.
27. Soheilian B. Paparoditis N. & Vallet B.: Detection and 3D reconstruction of traffic signs from multiple view color images. ISPRS Journal of Photogrammetry and Remote Sensing 2013Vol. 77 pp. 1-20 DOI:10.1016/j. isprsjprs.2012.11.009.
28. Sondej M Iwicki P.; Wojcik M. et al.: Stability analyses of a cylindrical steel silo with corrugated sheets and columns. Steel and Composite Structures 2016 Vol. 20 Iss. 1 pp. 147-166 DOI: 10.12989/scs.2016.20.1.147
29. Szeliski R.: Computer Vision Algorithms and Applications. Springer-Verlag London UK 2011.
30. Tejchman J. Wojcik M.: Modelling of shear localization during confined granular flow in silos within non-local hypoplasticity. Powder Technology 2009Vol. 192 iss. 3 pp.298-310 DOI: 10.1016/j.powtec.2009.01.021
31. Unger J. Reich M. & Heipke C.: UAV-based photogrammetry: monitoring of a building zone 2014. The International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences Vol. XL-5 2014 ISPRS Technical Commission V Symposium 23-25 June 2014 Riva del Garda Italy.
32. Wang L. Liu Z. & Zhang Z.: Efficient image features selection and weighting for fundamental matrix estimation. IET Computer Vision 2016 Vol. 10 Iss. 1 pp. 67-78 DOI: 10.1049/iet-cvi.2014.0436.
33. Zhang Z.Y.: Robust wide-baseline stereo from maximally stable extremal regions. International Journal of Computer Vision 1998 Vol. 27 Iss. 2 pp. 161-195.