The Transregional Collaborative Research Centre 161 “Quantitative Methods for Visual Computing” is an interdisciplinary research centre at the University of Stuttgart and the University of Konstanz, funded by Deutsche Forschungsgemeinschaft (DFG) under project number 251654672. Ulm University and Ludwig-Maximilians-Universität München are participating institutions in the second and third funding period. The Max Planck Institute for Biological Cybernetics in Tübingen in was a participating institution in the first funding period.

The goal of SFB/Transregio 161 is establishing the paradigm of quantitative science in the field of visual computing, which is a long-term endeavour requiring a fundamental research effort broadly covering four research areas, namely quantitative models and measures, adaptive algorithms, interaction and applications. In the third funding period, which started in 2023, new research directions are being approached. One is visual explainability, assessing and quantifying how well the users of a visualisation system understand the phenomena shown visually. The second direction targets mixed reality, covering all forms of augmented and virtual reality as a cross-cutting field of various visual computing subfields, irrespective of applied technology. The third research theme aims to bring research results in the world, moving away from experiments in the laboratory and in the wild to openly accessible applications that provide research results, methods, data sets, and other outcomes from SFB/Transregio 161 to a wide range of stakeholders in academia, industry, teaching, and society in general.

In SFB/Transregio 161, approximately 40 scientists in the fields of computer science, visualisation, computer vision, human computer interaction, linguistics and applied psychology are jointly working on improving the quality of future visual computing methods and applications.

Featured Dataverses

In order to use this feature you must have at least one published or linked dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

Advanced Search

11 to 20 of 29 Results
SFB-TRR 161 C07 "Optimization for Dynamic Mixed Reality User Interfaces" logo
Aug 4, 2023
In this project we aim to dynamically adapt the user interface during interaction with Cross-Reality (XR) applications through head-mounted displays (HMDs), to improve usability and ensure the users safety and comfort.
SFB-TRR 161 D02 "Evaluation Metrics for Visual Analytics in Linguistics" logo
Aug 4, 2023
Within linguistics, the use of large sets of data via a combination of rule-based and stochastic methods is now standardly part of the analysis of language structure. However, though scatter plots, bar or pie charts, and trees as provided by R, for example, are standardly used, n...
SFB-TRR 161 D03 "Visual Exploration and Analysis of Provenance Data" logo
Aug 4, 2023
To analyse or debug complex data processing applications, or to ensure their understandability and repeatability, provenance techniques are increasingly being deployed, resulting in large volumes and a wide variety of provenance data. The long-term goal of this project is to leve...
SFB-TRR 161 B05 "Efficient Large Scale Variational 3D Reconstruction" logo
Dec 16, 2021
The central goal of the project is to research and develop high-performance variational methods for large scale 3D reconstruction problems, which are general and accurate while meeting computation time constraints imposed by visual computing applications.
SFB-TRR 161 A03 "Quantification of Visual Analytics Transformations and Mappings" logo
Dec 16, 2021
High-dimensional data analysis requires dealing with numerous challenges, such as selecting meaningful dimensions, finding relevant projections, and removing noise. As a result, the extraction of relevant and meaningful information from high-dimensional data is a difficult proble...
SFB-TRR 161 B07 "Computational Uncertainty Quantification" logo
Dec 14, 2021
SFB-TRR 161 A01 "Uncertainty Quantification and Analysis in Visual Computing" logo
Dec 10, 2021
Add Data

Log in to create a dataverse or add a dataset.

Share Dataverse

Share this dataverse on your favorite social media networks.

Link Dataverse
Reset Modifications

Are you sure you want to reset the selected metadata fields? If you do this, any customizations (hidden, required, optional) you have done will no longer appear.