Geometric monitoring of the Bremen Cog
Beginn: 2017
Books and Papers
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Reznicek, J.; Luhmann, T.; Hastedt, H.; Jepping, C. (2016):
Influence of raw image preprocessing and other selected processes on accuracy of close-range photogrammetric systems according to VDI 2634. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLI-B5, 107-113
, doi: 10.5194/isprs-archives-XLI-B5-107-2016
Wichmann, Andreas; Kada, Martin (2016):
Joint Simultaneous Reconstruction of Regularized Building Superstructures from Low-Density LiDAR Data Using ICP. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
, doi: https://doi.org/10.5194/isprs-annals-III-3-371-2016 , Weblink
Jepping, C.; Schulz, J.-U.; Luhmann, T. (2016):
Konzept zur Modellierung kinematischer Rotorblattverformungen an Windkraftanlagen. Allgemeine Vermessungsnachrichten (AVN), 1, 3-10
Luhmann, T. (2016):
Learning Photogrammetry with Interactive Software Tool PhoX. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLI-B6, 39-44
, doi: 10.5194/isprs-archives-XLI-B6-39-2016
Jung, Jaewook; Sohn, Gunho; Bang, Kiin; Wichmann, Andreas; Armenakis, Costas; Kada, Martin (2016):
Matching Aerial Images to 3D Building Models Using Context-Based Geometric Hashing. Sensors
, doi: https://doi.org/10.3390/s16060932 , Weblink
Presentations
Luhmann, T.
:
Modelling of Chromatic Aberration for High Precision Photogrammetry.
Symposium ISPRS Commission V, Dresden,
September 2006
Luhmann, T.
:
4D Surface Matching for High-Speed Stereo Sequences.
Symposium ISPRS Commission V, Dresden,
September 2006
Luhmann, T.
:
High Precision Photogrammetry Using RGB Colour Information.
Coordinate Measurement Systems Conference, Orlando, Florida,
Juli 2006
Brinkhoff, T.
:
Towards a Sustainable e-Learning Solution for GI-Education.
ISPRS TC VI Symposium „e-Learning and the Next Steps for Education“, Tokyo, Japan,
Juni 2006
Projects
funded by: German Maritime Museum, Leibniz Institute for Maritime History
The project focusses on the conception and implementation of the geometric monitoring of the Bremen Cog (appr. 25m x 8m x 8m). The Bremen Cog is the best preserved medieval merchant ship in the world. A large-volume optical 3D-measurement con... more
funded by: Niedersächsisches Vorab
This interdisciplinary project aims to develop autonomous underwater and surface vehicles. One subproject focusses on the development of calibration procedures and algorithms for the special challenges of underwater photogrammetry. Another subproject... more
people
Prof. Dr.-Ing. habil. Dr. h.c. Thomas Luhmann (head) Prof. Dr. Thomas Brinkhoff (head) Robin Rofallski, M.Sc. (01.2017-12.2020) Tobias Werner, M.Sc. (02.2017-06.2020)
Prof. Dr.-Ing. habil. Dr. h.c. Thomas Luhmann (head) Prof. Dr. Thomas Brinkhoff (head) Robin Rofallski, M.Sc. (01.2017-12.2020) Tobias Werner, M.Sc. (02.2017-06.2020)
funded by: European Fonds for Regional Development (EFRE)
Dieses Forschungsvorhaben befasst sich mit der Entwicklung eines kompakten Prototyps zur hochgenauen berührungslosen 3D-Oberflächenvermessung unter Wasser durch den Einsatz optischer 3D-Messverfahren. more
people
Prof. Dr.-Ing. habil. Dr. h.c. Thomas Luhmann (head) Oliver Kahmen, M.Sc. Paul Kalinowski, M.Sc. Niklas Haase, M.Sc.
Prof. Dr.-Ing. habil. Dr. h.c. Thomas Luhmann (head) Oliver Kahmen, M.Sc. Paul Kalinowski, M.Sc. Niklas Haase, M.Sc.
Bachelor & Master Theses
Untersuchungen zum Einsatzpotential von UAV-Photogrammetrie bei der topographischen Ermessung im Vergleich zur klassischen Tachymeter-/GNSS-Vermessung (2024/1)
Untersuchung eines lidargestützten Verfahrens zur Detektion von dynamischen Hindernissen und Algorithmen zur Kollisionsvermeidung für die vollautomatische Navigation mit einem Autonomous Surface Vehicle (2024/1)
Entwicklung eines Dashboards zur Verbesserung des Bewerbungsprozesses für Unternehmen und Bewerber (2024/1)
cooperation
Human-Centered Design in der Konzeption und Entwicklung eines geodatenbasierten Entsiegelungskatasters (2023/12)
Flächendeckende Versiegelungsdetektion mittels Machine Learning für Entsiegelungskataster (2023/12)