The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIII-B2-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 259–266, 2022
https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-259-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 259–266, 2022
https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-259-2022
 
30 May 2022
30 May 2022

PORTABLE MULTI-CAMERA SYSTEM: FROM FAST TUNNEL MAPPING TO SEMI-AUTOMATIC SPACE DECOMPOSITION AND CROSS-SECTION EXTRACTION

L. Perfetti1, A. Elalailyi2, and F. Fassi1 L. Perfetti et al.
  • 1Politecnico di Milano, Dept. of Architecture, Built environment and Construction engineering (ABC), Italy
  • 2Politecnico di Milano, Italy

Keywords: Multi-camera, Photogrammetry, MMS, Tunnel, Mining, Shape decomposition, 3D Skeleton, Cross-section

Abstract. The paper outlines the first steps of a research project focused on the digitalization of underground tunnels for the mining industry. The aim is to solve the problem of rapidly, semi-automatically, efficiently, and reliably digitizing complex and meandering tunnels. A handheld multi-camera photogrammetric tool is used for the survey phase, which allows for the rapid acquisition of the image dataset needed to produce the 3D data. Moreover, since often, automatic, and fast acquisitions are not supported by easy-to-use tools to access and use the data at an operational level, a second aim of the research is to define a method able to arrange and organise the gathered data so that it would be easily accessible. The proposed approach is to compute the 3D skeleton of the surveyed environment by employing tools developed for the analysis of vascular networks in medical imagery. From the computed skeletonization of the underground tunnels, a method is proposed to automatically extrapolate valuable information such as cross-sections, decomposed portions of the tunnel, and the referenced images from the photogrammetric survey. The long-term research goal is to create an effective workflow, both at the hardware and software level, that can reduce computation times, process large amounts of data, and reduce dependency on high levels of experience.