Deep Learning Methods for Extracting Object-Oriented Models of Building Interiors from Images

Lars Obrock () and Eberhard Gülch
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Lars Obrock: Hochschule für Technik Stuttgart
Eberhard Gülch: Hochschule für Technik Stuttgart

Chapter 17 in iCity. Transformative Research for the Livable, Intelligent, and Sustainable City, 2022, pp 267-279 from Springer

Abstract: Abstract In this chapter, we present an approach of enriching photogrammetric point clouds with semantic information extracted from images of digital cameras or smartphones to enable a later automation of BIM modelling with object-oriented models. Based on the DeepLabv3+ architecture, we extract building components and objects of interiors in full 3D. During the photogrammetric reconstruction, we project the segmented categories derived from the images into the point cloud. Based on the semantic information, we align the point cloud, correct the scale and extract further information. The combined extraction of geometric and semantic information yields a high potential for automated BIM model reconstruction.

Keywords: Semantic modelling; BIM; Point clouds (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-92096-8_17

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DOI: 10.1007/978-3-030-92096-8_17

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