Oliver Kahmen, M.Sc.

Provenance and Collection Research Digital
mail:
tel: +49 (0) 441 - 7708 - 3349
room: G 207

Books and Papers

Kahmen, O.; Rofallski, R.; Luhmann, T. (2020): Impact of Stereo Camera Calibration to Object Accuracy in Multimedia Photogrammetry. Remote Sensing , doi: 10.3390/rs12122057 , Weblink
Kahmen, O.; Haase, N.; Luhmann, T. (2020): Orientation of point clouds for complex surfaces in medical surgery using trinocular visual odometry and stereo orb-slam2. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 35–42, 2020 , doi: 10.5194/isprs-archives-XLIII-B2-2020-35-2020 , Weblink

Presentations

Kahmen, O. : On scale definition within calibration and orientation of multi-camera systems in multimedia photogrammetry. Underwater 3D Recording & Modelling, ISPRS Commission II - WGII/9, Limassol, Cyprus, Mai 2019
Kahmen, O. : Hochauflösende 3D-Rekonstruktion von Schweißnähten mittels Makrophotogrammetrie. 6. Fachseminar der DGZfP, Optische Prüf- und Messverfahren, Karlsruhe, März 2019
Kahmen, O. : Optimierung flächenbasierter Bildzuordnungsverfahren bei spekularen Reflexionen. 18. Oldenburger 3D-Tage, Februar 2019

Projects

funded by: zukunft.niedersachsen
There are hundreds of thousands of artefacts in German museums that were brought to Europe during the colonial era as a result of wars, looting or trade. The history of these objects - where they came from, what they were used for and who once owned ... more
funded by: Federal Ministry for Economic Affairs and Climate Action
The goal of the project is to supplement the classic visual inspection (VT) of welded joints under water with an optical 3D measurement system. Based on high-resolution 2D (image) data, metric 3D (surface) data will be generat... more
funded by: Bundesministerium für Bildung und Forschung
The Project – „CoSAIR – Collaborative Spatial Artificial Intelligence in Realtime“ is funded by the Federal Ministry of Education and Research within the program „Research at Universities of Applied Sciences“ in order to create, consolida... more

Bachelor & Master Theses


Bildbasierte Detektion von Rissen in Schweißverbindungen mit den Methoden des Deep Learnings (2022/10)
Untersuchung verschiedener Bildanalyseverfahren zur Orientierung von Bildsequenzen eines Dreikamerasystems (2020/2)
Entwicklung eines Prozesses zur Detektion von Rissen auf Schweißnähten durch digitale Bildverarbeitung (2020/1)
Untersuchung von Orientierungs- und Matchingverfahren für die hochgenaue 3D-Oberflächenerfassung von Schweißnähten mit einem mobilen Kamerasystem (2018/9)