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 goal of this project is to enable a reliable decision support for large-scale infrastructure projects by providing solutions for a collaborative visual analysis of digital twins.
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.
The "Mars-DL" project is investigating how a deep learning system can support the research work of planetary scientists through object and pattern recognition. For this project VRVis has extended the functionality of PRo3D to automatically render shatter cone training images.
MINERVA is an integrated framework for planetary scientists allowing members of different instrument teams to cooperate synergistically in virtual workspaces by sharing observations, analyses and annotations of heterogonous mission data.
Visual Analysis of Asteroid Deflection.
In this project tools and methods for handling, administration, manipulation and evaluation of several different data sources for measurements and lighting design are developed.
In this project we develop new methods from the field of visual analysis and machine learning to automate the quality control and quality assurance of glass articles.
Research project on powerful visualization methods to support decision making in complex infrastructure projects, especially in tunnel, railway and road construction.
Visualization and visual analysis of high-resolution surface reconstructions find a wide range of applications, from tunnel monitoring and archaeological excavations to the change management of cultural heritage buildings.
Digital representations of the real world and digital twins are becoming increasingly important for planning, situation assessment and decision-making.
Virtual exploration and geological analysis of reconstructed Mars surfaces and rock outcrops.
Support for planetary research: Visual analysis of reconstructions of the Mars surface and view planning for rover camera instruments.
A visual tool for a combined stratigraphic and temporal documentation and interpretation of excavation projects.
Strategic Research in Scalable, Semantic Rendering.
Planetary Robotics Vision Data Exploitation.
Investigation of techniques enabling a seamless analysis of data from multi-run simulations on multiple degrees of detail.
Seamless visual analysis of data involving 3D geometry, relational information and multivariate attributes.
Algorithms to improve the visual analysis of surface reconstructions.
High-quality lighting simulation requires dynamic, interactive, realistic real-time lighting simulation for various complex architectural environments.
Visual Analytics for Modeling and Simulation: Improvement of simulation setup and design scenarios with tools and methods of Visual Analytics.
Decision support systems and 3D viewing technologies for tunnel construction.