Books and Papers

Perda, G.; Morelli, L.; Remondino, F.; Fraser, C.; Luhmann, T. (2024): Analyzing marker-based, handcrafted and learning-based methods for automated 3D measurement and modelling. Optical 3D Metrology Workshop, Brescia
Paulau, P.; Hurka, J.; Middelberg, J.; Koch, S. (2024): Centralised monitoring and control of buildings using open standards. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences , doi: 10.5194/isprs-annals-X-4-W4-2024-169-2024 , Weblink
Sheikholeslami, Mohammad Moein; Kamran, Muhammad; Wichmann, Andreas; Sohn, Gunho (2024): CornerRegNet: Building Segmentation from Overhead Imagery Using Oriented Corners in Deep Networks. Proceedings of the IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
Sieberth, T.; Meindl, Michael; Sagmeiser, Bernhard; Franckenberg, Sabine; Ptacek, Wolfgang (2024): Cost-effective 3D documentation device in forensic medicine. Forensic Science International , doi: https://doi.org/10.1016/j.forsciint.2024.112005
Sheikholeslami, Mohammad Moein; Kamran, Muhammad; Wichmann, Andreas; Sohn, Gunho (2024): Enhancing Polygonal Building Segmentation via Oriented Corners. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , doi: https://doi.org/10.48550/arXiv.2407.12256 , Weblink

Presentations

Nietiedt, S. : Simulation-based accuracy investigation of a photogrammetric setup to measure a dynamic process. Optical 3D Metrology workshop (O3DM), Dezember 2022 doi: https://doi.org/10.5194/isprs-archives-XLVIII-2-W2-2022-95-2022
Luhmann, T. : Dynamic optical 3D metrology for wind energy applications. Optical 3D Metrology (O3DM), Würzburg, Dezember 2022
Luhmann, T. : Optische 3D-Messtechnik im Kontext von Industrie 4.0. Technische Universität Dresden, Dezember 2022
Jaquemotte, I. ; Pesch, R. : Möglichkeiten der Einbindung des Landschaftsinformationszentrums Ammerland e.V. in die Lehrveranstaltungen des Abteilung Geoinformation des Fachbereichs BGG der Jade Hochschule. Roadmap Geografische Forschungsthemen im Ammerland; Landschaftsinformationszentrum Ammerland e.V., Jaspershof, Westerstede, November 2022
Luhmann, T. : Development of a simulator for terrestrial laser scanning as a powerful tool for distance learning. Polytecnico di Milano, Campus Lecco, November 2022

Projects

funded by: Niedersächsisches Vorab
The collection of the State Museum Nature and Man Oldenburg includes objects from natural history, archaeology and ethnology. Only a small proportion of the objects has been digitally acquired and made virtually accessible so far. Digitalisation (... more
people
Prof. Dr.-Ing. habil. Dr. h.c. Thomas Luhmann (head) Simon Albers, M.Sc. (10.2022-03.2023) Paul Kalinowski, M.Sc.
funded by: Bundesministerium für Bildung und Forschung
A decarbonized heat supply in urban areas in the future poses a particular challenge. The technical focus on the system coupling of electricity and heat production to increase the share of renewable energies in the heat supply alone will not be suffi... more
people
Prof. Dr. Jürgen Knies (head) (03.2019-12.2019) Prof. Dr. Sascha Koch (head) (03.2020-) Sebastian Erdmann, M.Sc. (10.2020-07.2021) Marvin Schnabel, M.Sc. (01.2022-)
funded by: European Fonds for Regional Development (EFRE)
The aim of the collaborative project is the simultaneous geometric recording of turbulent wind flow fields (fluid behaviors) and deformations of rotor blade surfaces of wind energy systems. This helps to generate new knowledge about the influ... more
people
Prof. Dr.-Ing. habil. Dr. h.c. Thomas Luhmann (head) Sinah Vogel (01.2021-04.2021) Dr. Ing. Thomas Willemsen (10.2018-06.2019) Simon Nietiedt, M.Sc. Annika Katrin Jepping, B.Sc. Martina Göring, M.Sc. Robin Rofallski, M.Sc.

Bachelor & Master Theses


Augmented Reality in der Flurbereinigung: Untersuchung zur Visualisierung der Besitzeinweisung (2024/2)
supervisors

Prof. Dr. Ingrid Jaquemotte

Dr. Andre Riesner

Untersuchung zur Georeferenzierung und Nutzung von Urkarten des Liegenschaftskatasters (2024/2)
Analyse und Vergleich der geometrischen Eigenschaften von Referenzdaten und KI-Ergebnissen für die automatische Gebäudeerkennung in Luftbildern (2024/2)
Maschinelles Lernen für die Identifikation von baulichen Erweiterungen an Gebäuden anhand geometrischer Merkmale von ALKIS- und durch KI bestimmten Hausumringen (2024/2)
Integration und Verteilung von ALKIS-Grunddaten und Fortführungsdaten in Echtzeit mittels Open-Source-Technologien (2024/2)