Oliver Kahmen, M.Sc.

Digital visual testing on welds under water by high-resolution optical 3D surface reconstruction
Collaborative Spatial Artificial Intelligence in Realtime

tel: +49 (0) 441 - 7708 - 3349
room: G 207

Books and Papers

Kahmen, O.; Rofallski, R.; Luhmann, T. (2023): Digital visual testing of welds under water using optical 3D measurement technology with image-variant illumination. Unterwassertechnik 2023 - DVS Media, DVS Berichte, Band: 374, S. 93-101, ISBN: 978-3-96144-159-4 , Weblink
Rofallski, R.; Kahmen, O.; Luhmann, T. (2022): Investigating distance-dependent distortion in multimedia photogrammetry for flat refractive interfaces. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2/W2-2022, 127–134 , doi: 10.5194/isprs-archives-XLVIII-2-W2-2022-127-2022 , Weblink
Luhmann, T.; Rofallski, R.; Kahmen, O. (2022): Möglichkeiten und Grenzen der hochgenauen photogrammetrischen Objekterfassung unter Wasser. DVW/DHyG Fachtagung "Hydrographie - Messen mit allen Sinnen", Schriftenreihe des DVW, Band 102, pp. 109-116
Kahmen, O.; Luhmann, T. (2022): Monocular Photogrammetric System for 3D Reconstruction of Welds in Turbid Water. PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science, Vol. 90, Issue 1, pp. 19-35 , doi: 10.1007/s41064-022-00191-2
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. : Influence of Quantity, Size and Arrangement of Scale Bars in Large Volume Photogrammetry. EPMC European Portable Metrology Conference 2015, Manchester, Oktober 2015


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
funded by: European Fonds for Regional Development (EFRE)
The project objective is the investigation of imaging techniques and the development of special methods based on intraoperative and preoperative data. The field of application is primarily in orthopedics, however, in principle the problem can be tran... 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)