No blind spots on train roofs thanks to depth cameras.
WIBSTAC addresses the usage of wide baseline stereo 3D reconstruction for medium- and long-range mapping of the Martian surface, based on imagery from panoramic rover camera instruments.
With the help of 3D printing (additive manufacturing), spare parts for defective trains can be produced more easily and in a sustainable way as well as faster and cheaper - a great potential for the climate-friendly future of train transport companies.
Together with Rhomberg Bau GmbH and convex ZT GmbH, VRVis is developing a concept for the use of Boston Dynamic's robot dog "Spot" for autonomous, immersive construction site documentation.
The research goal of AMASE is to create a suite of tools and methods to ingest, process, visualize, and manipulate heterogeneous, large-scale geospatial data. This data is the constantly updated representation of the real world in the form of an evolving digital twin.
The main objective of the strategic project ARCS is the design of software architectures that enable interactive visualization systems to ingest large volumes and velocities of geospatial and associated non-geometric data.
Support for planetary research: Visual analysis of reconstructions of the Mars surface and view planning for rover camera instruments.
The applied research project Lightbox 2.0 focuses on the development of a photogrammetric 3D scanner for automatic and deep learning-based modeling of all kinds of keys.
In this project tools and methods for handling, administration, manipulation and evaluation of several different data sources for measurements and lighting design are developed.
Barrier-free access to art and museums for blind and visually impaired people through 3D technology.
Strategic Research in Scalable, Semantic Rendering.
Investigation of techniques enabling a seamless analysis of data from multi-run simulations on multiple degrees of detail.
Algorithms to improve the visual analysis of surface reconstructions.