Airborne Multi-Sensor; City Modelling; Geospatial Data; Laser Scanning; Photogrammetry; Registration; Airborne multi-sensor; City model; Data gap; Geo-spatial data; Laser scanning; Multi sensor; Multiple source; Point-clouds; Source points; Instrumentation; Environmental Science (miscellaneous); Earth and Planetary Sciences (miscellaneous)
Résumé :
[en] Point cloud fusion is a process plays pivotal role in geospatial data analysis that aims to integrate data from multiple sources to create a comprehensive and precise representation of the environment. Integrating point clouds acquired from cross-source or hybrid sensors presents unique challenges due to differences in geometric accuracy, precision, and the size of data gaps, along with variations in available attributes. Significant progress has been made in developing algorithms and methods to address these challenges, but the problems are not sufficiently resolved and remain one of the most challenging aspects of geospatial data processing. In this paper, we present a new approach for airborne cross-source point cloud fusion through a slice-to-slice adjustment. Our method generates cross-sectional slices and aligns them following some sequential steps. This approach enhances the accuracy and completeness of the fused point cloud, overcoming issues related to geometric disparities and data gaps. Experimental results demonstrate the effectiveness of our approach in improving registration accuracy, preserving geometric detail, and providing valuable insights for utilizing the potentials of both data sources.
Disciplines :
Ingénierie civile
Auteur, co-auteur :
PARVAZ, Shahoriar ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE)
TEFERLE, Félicia Norma Rebecca ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE)
NURUNNABI, Abdul Awal Md ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE)
Co-auteurs externes :
no
Langue du document :
Anglais
Titre :
Airborne Cross-Source Point Clouds Fusion by Slice-to-Slice Adjustment
Date de publication/diffusion :
31 mai 2024
Nom de la manifestation :
8th International Conference on Smart Data and Smart Cities (SDSC)
Lieu de la manifestation :
Athens, Grc
Date de la manifestation :
04-06-2024 => 07-06-2024
Manifestation à portée :
International
Titre du périodique :
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
This study is funded through Project No 17042266, DF4CM - Reporting/22/IS, Luxembourg National Research Fund (FNR). We also thank the Administration du Cadastre et de la topographie (ACT) for the Airborne oblique imagery and LiDAR dataset. Abdul Nurunnabi is funded through the IASAUDACITY- PIONEER-2022 project at the University of Luxembourg.
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