Generating 2D Building Floors from 3D Point Clouds

Conference Paper (2023)
Author(s)

Anh Thu Thi Phan (Ho Chi Minh City University of Technology (HCMUT), Vietnam National University)

Thi Ngoc Huynh (Ho Chi Minh City University of Technology (HCMUT), Vietnam National University)

Linh Truong-Hong (TU Delft - Civil Engineering & Geosciences)

Research Group
Optical and Laser Remote Sensing
DOI related publication
https://doi.org/10.1007/978-981-99-7434-4_179 Final published version
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Publication Year
2023
Language
English
Research Group
Optical and Laser Remote Sensing
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Pages (from-to)
1660-1668
Publisher
Springer
ISBN (print)
['9789819974337', '978-981-99-7436-8']
ISBN (electronic)
978-981-99-7434-4
Event
3rd International Conference on Sustainable Civil Engineering and Architecture, ICSCEA 2023 (2023-07-19 - 2023-07-21), Da Nang City, Viet Nam
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Abstract

Laser scanning (LS) is an effective technology for accurately capturing point clouds of visible surfaces of objects in 3D scenes. The point clouds were subsequently used for various applications, for example, generating 2D drawings of the floor or building information models (BIM) and structural inspection. However, in practice, the products from point cloud are created mainly by using commercial software, in which the quality primarily depends on users’ experiences and may contain the error caused by technician carelessness. This paper proposed a new method to automatically extract the point clouds of the floor and create a 2D drawing of floor slabs. This method analyses features of the points within cells of a 2D cell grid in the xy plane to extract candidate points of the building and each floor, while the cell- and point-based region growing segmentations were employed to extract the final points of the floor and each edge of the floor, respectively. The proposed method was successfully tested on 7.5 million points of a concrete, two-story building with 17 m long x 7m width x 7m height.

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