Research topics

All images and also data acquired by sensors can be converted into a digital representation. Digital twins are generated from real-world data, which serve as the basis for several digital applications. In our research work we focus on the fields of remote sensing and semantic reconstruction as well as on solutions for inclusive digitization and the medical sector.

Remote sensing enables us to obtain information about places or objects that would otherwise not be accessible and analyzable by recording spatial data. These can be rock walls or facades photographed by drone flight, as well as entire continents via satellite images or distant planets that can be reconstructed from measured data. We create solutions to adapt remote sensing methods for different industries. Our research results range from interactive visualization of the surface of Mars for planetary research/space travel to the generation of BIM models from existing scans of existing structures. The innovative bridging between data acquisition and semantic modelling is important to us.

In the field of semantic reconstruction, we are working, among other things, on finding efficient ways to automatically segment and classify buildings or other objects on images using computer vision algorithms and machine learning, in order to then "intelligently" reconstruct them as a three-dimensional model. This means, for example, that the 3D model of a house itself "recognizes" where its walls, doors, windows and so on are. Here, we optimize semi-automatic approaches that are controlled by the user on the one hand, and work on the other hand on the development of fully automatic methods.

In order to make the museums of the future barrier-free, we have been conducting intensive research for many years in the field of inclusive digitization to find IT-based solutions that can make the fine arts "visible" to all target groups. To this end, we have developed, among other things, special visualization software that creates a digital 2.5D model from 3D scans or photographs of museum objects. Using an innovative milling process, this model can be transformed into a tactile relief that makes heights, depths, surface structures, etc. haptically perceptible - thus equipping museums for the 21st century.

For the efficient further use and analysis of data obtained by imaging methods in the medical sector, we are researching innovative ways of automatically segmenting specific image content such as vertebrae, tumors or organs using machine learning and specially developed algorithms. This is an important supporting measure in the diagnostic process and also serves as a basis for reconstructions of volume data, for example.