- Titel
- Workflow automation for SfM change-detection
- Untertitel
- an application to rockfalls
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:14-qucosa2-985377
- Konferenz
- 5th Virtual Geoscience Conference. Dresden, 21. - 22. September 2023
- Quellenangabe
- VGC 2023 - Unveiling the dynamic Earth with digital methods
Herausgeber: Helmholtz-Institut Freiberg für Ressourcentechnologie
Herausgeber: Technische Universität Dresden
Erscheinungsort: Dresden
Erscheinungsjahr: 2023
Seiten: 46-47 - Erstveröffentlichung
- 2023
- DOI
- https://doi.org/10.25368/2025.176
- Abstract (EN)
- The workflow for change detection from point clouds is well known and used in various scientific fields for monitoring processes. This method was extensively developed in the last two decades with the introduction of LiDAR (Light Detection and Ranging) technology, which allows point clouds to be acquired with exceptional accuracy and speed. However, the advent of SfM-MVS (Structure from Motion - Multi-View Stereo) algorithms, which enables the generation of point clouds at very low cost, makes this method a suitable alternative and one of the most widely used tool for monitoring in the geosciences.
- Freie Schlagwörter (EN)
- Rockfall monitoring, change detection, machine learning, Structure from Motion
- Klassifikation (DDC)
- 550
- Klassifikation (RVK)
- RB 10081
- Herausgeber (Institution)
- Helmholtz-Institut Freiberg für Ressourcentechnologie, Freiberg
- Technische Universität Dresden, Dresden
- Version / Begutachtungsstatus
- publizierte Version / Verlagsversion
- URN Qucosa
- urn:nbn:de:bsz:14-qucosa2-985377
- Veröffentlichungsdatum Qucosa
- 18.08.2025
- Dokumenttyp
- Konferenzbeitrag
- Sprache des Dokumentes
- Englisch
- Lizenz / Rechtehinweis
CC BY 4.0