Fields of Activity / Competences
- Markov Random Field Models for Computer Vision
- Visual Correspondence Estimation (Stereo, Motion)
- Photomontage, Stitching
- Projective Geometry
- Software Development in C++ / Matlab
- Stephani, H.; Weibel, T.; Rösch, R.; Moghiseh, A.:
Challenges and approaches when realizing online surface inspection systems with deep learning algorithms.
Discover Data: Volume 1, Article number: 3 (2023)
- Müller, O.; Fend, C.; Moghiseh, A.; Schladitz, K.; Stephani, H.; Weibel, T.:
Deep learning for image based shelve inventories.
10th International Symposium on Signal, Image, Video and Communications, ISIVC 2020: Saint-Etienne, France, 7–9 April 2021. Piscataway, NJ: IEEE, 2021
- S. Ali, C. Daul, T. Weibel, and W. Blondel:
Fast mosaicing of cystoscopic images from dense correspondence: combined SURF and TV-L1 optical flow method.
In 20th International Conference on Image Processing (ICIP), pages 1291-1295, September 2013. Melbourne, Australien.
- T. Weibel, C. Daul, D. Wolf, R. Rösch, and F. Guillemin:
Graph based construction of textured large field of view mosaics for bladder cancer diagnosis.
Pattern Recognition, 45(12):4138 – 4150, 2012
- T. Weibel, C. Daul, D. Wolf, and R. Rösch:
Contrast-enhancing seam detection and blending using graph cuts.
In 21st International Conference on Pattern Recognition (ICPR), pages 2732–2735, November 2012. Tsukuba, Japan (Oral presentation)