UNCERTAINTY MODELING FOR POINT CLOUD-BASED AUTOMATIC INDOOR SCENE RECONSTRUCTION BY STRICT ERROR PROPAGATION ANALYSIS
Publikation: Beitrag in Fachzeitschrift › Konferenzartikel › Beigetragen › Begutachtung
Beitragende
Abstract
Accurate digital representation of indoor facilities is a key component for the generation of building twins. 3D indoor scenes are often reconstructed from 3D point clouds obtained by various measurement techniques, which usually show different accuracy characteristics. During the reconstruction process, the uncertainties of data and intermediate products propagate into the accuracy of the vectorized model. Although point clouds-based 3D building modeling has been a hot topic of research for at least two decades, a thorough analysis of error propagation for this problem from a geodetic point of view is still underrepresented. In this contribution, we propose an analytical approach to estimate the uncertainty of 3D modeling results using the analytic approach based on first-order Taylor-series expansion. A general model for the input data is established and the uncertainty expressions of all computed products are symbolically derived. We estimate the uncertainty of 3D data fitting, followed by the derivation of vectorized building parameters and their covariance matrices. The results of the theoretical approaches are tested on real data presenting an indoor scene. The practical example is illustrated, thoroughly analysed, and quantified.
Details
Originalsprache | Englisch |
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Seiten (von - bis) | 395-400 |
Seitenumfang | 6 |
Fachzeitschrift | International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives |
Jahrgang | 43 |
Ausgabenummer | B2-2022 |
Publikationsstatus | Veröffentlicht - 30 Mai 2022 |
Peer-Review-Status | Ja |
Konferenz
Titel | 2022 24th ISPRS Congress on Imaging Today, Foreseeing Tomorrow, Commission II |
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Dauer | 6 - 11 Juni 2022 |
Stadt | Nice |
Land | Frankreich |
Schlagworte
ASJC Scopus Sachgebiete
Schlagwörter
- Building reconstruction, Error propagation, Indoor 3D models, Taylor series, Uncertainty modeling