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Internet photogrammetry for inspection of seaports

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Języki publikacji
EN
Abstrakty
EN
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.
Rocznik
Tom
S 1
Strony
174--181
Opis fizyczny
Bibliogr. 33 poz., rys., tab.
Twórcy
autor
  • Univeristy of Wamia and Mazury in Olsztyn Faculty of Geodesy, Geospatial and Civil Engineering, Oczpowskiego 2, 10-718 Olsztyn Poland
autor
  • Univeristy of Wamia and Mazury in Olsztyn Faculty of Geodesy, Geospatial and Civil Engineering, Oczpowskiego 2, 10-718 Olsztyn Poland
autor
  • Gdansk University of Technology Faculty of Civil and Environmental Engineering, Narutowicza 11/12, 80-233 Gdansk Poland
Bibliografia
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  • 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
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  • 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 , 2013,Vol. 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, 2009,Vol. 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.
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-8b18b17d-5a6e-4736-a050-b40abaf8e959
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