Research Group of Prof. Dr. Martin Rumpf
Research Projects
Current
Numerical optimization of shape microstructures
Project C06, DFG SFB 1060.
Completed
4D structural analysis of the sugar beet geometry
Project D4, BMBF competence network.
Our goal is developing techniques for model-based 3D reconstruction and classification of storage root geometry from tomographic data, i.e. data obtained from laser scans and MRI. We aim in comparing different cultivars subject to different soil, management and environmental conditions. Furthermore we investigate the temporal variation of sugar beet growth by applying and generalizing regression methods to the space of beets.
Our tools are robust and non-supervised, that means they improve previous and-measured methods and corresponding empirical scales. Furthermore, recent results suggest that our methods are capable to statistically separate genotypic from environmental features. Hence the proposed techniques are relevant and effective tools to optimize plant breeding.
Anisotropic Curvature Flows in Surface Modeling
Mathematical modeling and simulation of microstructured magnetic-shape-memory materials
Project A6, DFG priority program 1239.
Morphological Non-Rigid Registration
Multi-Scale Shape Optimization under Uncertainty
Segmentation with adaptive Level Set methods
