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Towards automatic defects analyses for 3D structural monitoring of historic timber
Chizhova, Maria; Pan, Junquan; Luhmann, Thomas; u. a. (2024): Towards automatic defects analyses for 3D structural monitoring of historic timber, in: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Katlenburg-Lindau: Copernicus GmbH, S. 103–110, doi: 10.5194/isprs-archives-xlviii-2-w4-2024-103-2024.
Author:
Title of the Journal:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
ISSN:
2194-9034
Conference:
10th Intl. Workshop 3D-ARCH “3D Virtual Reconstruction and Visualization of Complex Architectures”, 21–23 February 2024 ; Siena, Italy
Publisher Information:
Year of publication:
2024
Volume:
XLVIII-2/W4-2024
Pages:
Language:
English
Abstract:
Stability of historic wooden constructions is changing with time and should be inspected appropriately for risk assessment and prevention. The stability or strength values of built-in historic timber are difficult or even impossible to be derived without invasive investigation, but this is particularly problematic for the monitoring of heritage objects. Luckily there are some visible timber surface features, like knots and cracks, which can act as individual evidence to estimate the wood strength as well as to adjust its grade class indicator. In the final project, we aim to compare different approaches for 3D digital documentation of historic wood timbers and focus on automatic knot detection using AI techniques. A first feasibility study reported here provides a scientific baseline for the development of an automated method to analyse historic timber stability using 3D surveying and recognised surface features. First results about texture and resolution properties are discussed here.
GND Keywords: ; ; ; ;
Bauholz
Bauwerk
Analyse
3D-Scanner
Denkmalkunde
Keywords: ; ; ; ; ; ;
historic wooden timber
feature extraction
machine learning
3D scanning
structure from motion
multi view photometric stereo
reflectance transformation imaging
DDC Classification:
RVK Classification:
Peer Reviewed:
Yes:
International Distribution:
Yes:
Open Access Journal:
Yes:
Type:
Conferenceobject
Activation date:
February 26, 2024
Versioning
Question on publication
Permalink
https://fis.uni-bamberg.de/handle/uniba/93607