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Articles | Volume XLIII-B2-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 605–612, 2021
https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-605-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 605–612, 2021
https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-605-2021

  28 Jun 2021

28 Jun 2021

INDOOR MAPPING OF A COMPLEX CULTURAL HERITAGE SCENE USING TLS AND HMLS LASER SCANNING

V. E. Oniga1,2, A. I. Breaban1, E. I. Alexe1, and C. Văsii3 V. E. Oniga et al.
  • 1Department of Terrestrial Measurements and Cadastre, Faculty of Hydrotechnical Engineering, Geodesy and Environmental Engineering, „Gheorghe Asachi” Technical University of Iasi, Professor Dimitrie Mangeron Boulevard 67, 700050, Iasi, Romania
  • 2Romanian Society of Photogrammetry and Remote Sensing, Lacul Tei Blvd. 124, 020396, Bucharest, Romania
  • 3S.C. Helmert S.R.L, I.S. Sturza Boulevard 27, 600269, Bacau, Romania

Keywords: Terrestrial laser scanner, Point cloud, Registration, Hand-held Mobile laser scanner, Accuracy

Abstract. Indoor mapping and modelling is an important research subject with application in a wide range of domains including interior design, real estate, cultural heritage conservation and restoration. There are multiple sensors applicable for 3D indoor modelling, but the laser scanning technique is frequently used because of the acquisition time, detailed information and accuracy. In this paper, the efficiency of the Maptek I-Site 8820 terrestrial scanner, which is a long-range laser scanner and the accuracy of a HMLS point cloud acquired with a mobile scanner, namely GeoSlam Zeb Horizon were tested for indoor mapping. Aula Magna “Carmen Silva” of the “Gheorghe Asachi” Technical University of Iasi is studied in the current paper since the auditorium interior creates a distinct environment that combines complex geometric structures with architectural lighting and for preserving its great cultural value, the monument has a national historical significance. The registration process of the TLS point clouds was done using two methods: a semi-automatic one with artificial targets and a completely automatic one, based on Iterative Closest Point (ICP) algorithm. The resulted TLS point cloud was analysed in relation to the HMLS point cloud by computing the M3C2 (Multiscale Model to Model Cloud Comparison), obtaining a standard deviation of 2.1 cm and by investigating the Hausdorff distances from which resulted a standard deviation (σ) of 1.6 cm. Cross-sections have been extracted from the HMLS and TLS point clouds and after comparing the sections, 80% of the sigma values are less or equal to 1 cm. The results show high potential of using HMLS and also a long-range laser scanner for 3D modelling of complex scenes, the occlusion effect in the case of TLS being only 5% of the scanned area.