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3D Modelling of Cylindrical-Shaped Objects From Lidar Data - an Assessment Based on Theoretical Modelling and Experimental Data

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Despite the increasing availability of measured laser scanning data and their widespread use, there is still the problem of rapid and correct numerical interpretation of results. This is due to the large number of observations that carry similar information. Therefore, it is necessary to extract from the results only the essential features of the modelled objects. Usually, it is based on a process using filtration, followed by simplification and generalization of redundant contents of datasets. This process must ensure the collection of new data without loss of information contained therein, the description accuracy of the key features of a measured object, as well as the uniqueness and comparability of results. In this paper, the authors extend the already extensive range of algorithms for the automatic or semiautomatic modelling of cylindrical objects, which have been measured using the laser scanning technology, with the one employing a concave hull or - in general - the alpha-shape (α-shape). The applicability of the proposed method was analysed using simulated data - generated analytically with the introduced and established systematic error with normal distribution - and using real results of the measurement of cylindrical-shaped objects. For real data, the obtained results were compared with the reference data. This made it possible to determine the validity of the proposed new method.
Rocznik
Strony
47--56
Opis fizyczny
Bibliogr. 20 poz., rys., tab., wykr., wzory
Twórcy
autor
  • University of Warmia and Mazury in Olsztyn, Faculty of Geodesy, Geospatial and Civil Engineering, M. Oczapowskiego 2, 10-719 Olsztyn, Poland
autor
  • Gdańsk University of Technology, Faculty of Civil and Environmental Engineering, G. Narutowicza 11/12, 80-233 Gdańsk, Poland
autor
  • Gdańsk University of Technology, Faculty of Civil and Environmental Engineering, G. Narutowicza 11/12, 80-233 Gdańsk, Poland
Bibliografia
  • [1] Amirian, P., Basiri, A., Winstanley, A. (2013). Efficient Online Sharing of Geospatial Big Data Using NoSQL XML Databases. 2013 Fourth International Conference on Computing for Geospatial Research and Application , 152-152.
  • [2] Janowski, A., Rapiński, J. (2013). M-split estimation in laser scanning data modeling. J. Indian Soc. Remote Sens., 41(1), 15-19.
  • [3] Tomljenovic, I., Rousell, A. (2014). Influence of point cloud density on the results of automated Object-Based building extraction from ALS data. AGILE Conference Castellon.
  • [4] Burdziakowski, P., Janowski, A., Kholodkov, A, et al. (2015). Maritime laser scanning as the source for spatial data. Pol. Mar. Res., 22(4), 9-14, 2015.
  • [5] Janowski, A., Nagrodzka-Godycka, K., Szulwic, J., Ziółkowski, P. (2016). Remote sensing and photogrammetry techniques in diagnostics of concrete structures. Comput. Concr., 18(3), 405-420.
  • [6] Janowski, A., Szulwic, J., Zuk, M. (2015). 3D modelling of liquid fuels base infrastructure for the purpose of visualization and geometrical analysis. 15th International Multidisciplinary Scientific GeoConference SGEM 2015, www.sgem.org, SGEM2015 Conference Proc. , 1, 753-764.
  • [7] Bobkowska, K., Inglot, A., Mikusova, M. et al. (2017). Implementation of spatial information for monitoring and analysis of the area around the port using laser scanning techniques. Pol. Mar. Res., 24(SI1), 10-15.
  • [8] Szulwic, J., Tysiac, P., Wojtowicz, A. (2016). Coastal cliffs monitoring and prediction of displacements using terrestial laser scanning. Baltic Geodetic Congress (Geomatics), 61-66.
  • [9] Bobkowska, K., Janowski, A., Przyborski, M., Szulwic, J. (2016). Analysis of high resolution clouds of points as a source of biometric data. Baltic Geodetic Congress (Geomatics), 15-21.
  • [10] Majchrowski, R., Grzelka, M., Wieczorowski, M., Sadowski, Ł., Gapiński, B. (2015). Large area concrete surface topography measurements using optical 3D scanner. Metrol. Meas. Syst., 22(4), 565-576.
  • [11] Liu, X., Zhang, Z. (2008). LiDAR data reduction for efficient and high quality DEM generation. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 37, 173-178.
  • [12] Lin, X., Zhang, J. (2014). Segmentation-based filtering of airborne LiDAR point clouds by progressive densification of terrain segments. Remote Sens., 6(2), 1294-1326.
  • [13] Zhu, N., Jia, Y., Luo, L. (2016). Tunnel point cloud filtering method based on elliptic cylindrical model. International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences, 41(B1), 735-740.
  • [14] Huang, H., Brenner, C., Sester, M. (2013). A generative statistical approach to automatic 3D building roof reconstruction from laser scanning data. ISPRS J. Photogramm. Remote Sens., 79, 29-43.
  • [15] Xiong, X., Adan, A., Akinci, B., Huber, D. (2013). Automatic creation of semantically rich 3D building models from laser scanner data. Autom. Constr., 31, 325-337.
  • [16] Zhu, L., Hyyppa, J. (2014). The Use of Airborne and Mobile Laser Scanning for Modeling Railway Environments in 3D. Remote Sens., 6(4), 3075-3100.
  • [17] Akkiraju, N., Edelsbrunner, H., Facello, M., Fu, P., Mucke, E.P., Varela, C. (1995). Alpha shapes definition and softwar. Internat.Comput. Geom. Software Workshop.
  • [18] Niedostatkiewicz, M., Tejchman, J., Chaniecki, Z., et al. (2009). Determination of bulk solid concentration changes during granular flow in a model silo with ECT sensors. Chemical Engineering Science, 64(1), 20-30.
  • [19] Wojcik, M., Sondej, M., Rejowski, K., et al.. (2017). Full-scale experiments on wheat flow in steel silo composed of corrugated walls and columns. Powder Technology, 311, 537-555.
  • [20] Rapinski, J., Janowski, A. (2016). Algorithm for Staking Out Interior Elements of the Wind Turbine Monopile. J. Surv. Eng., 04016029.
Uwagi
PL
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-5a297d41-c26d-4305-86ce-d11ac269256c
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