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

41 to 50 of 69 Results
Aug 31, 2022 - SFB-TRR 161 B04 "Adaptive Algorithms for Motion Estimation"
Mehl, Lukas; Beschle, Cedric; Barth, Andrea; Bruhn, Andrés, 2022, "Replication Data for: An Anisotropic Selection Scheme for Variational Optical Flow Methods with Order-Adaptive Regularisation",, DaRUS, V1
Results of our proposed optical flow method on the Sintel and KITTI datasets. We provide the benchmark results before and after applying our refinement approach. Additionally, we provide a supplementary material to our paper with more details on the minimisation, the numerical so...
Aug 24, 2022 - SFB-TRR 161 A02 "Quantifying Visual Computing Systems"
Müller, Christoph; Heinemann, Moritz; Weiskopf, Daniel; Ertl, Thomas, 2022, "Energy consumption of scientific visualisation and data visualisation algorithms",, DaRUS, V1, UNF:6:dEyIoAgP890tWqA/WShryw== [fileUNF]
This data set comprises a series of measurements of GPU power consumption when raycasting spherical glyphs, raycasting scalar fields and when showing web-based data visualisation on Observable HQ. The data sets for sphere rendering were: pos_rad_intensity : 500000 : 0 : 10 10 10...
Aug 8, 2022 - SFB-TRR 161 A01 "Uncertainty Quantification and Analysis in Visual Computing"
Hägele, David; Krake, Tim, 2022, "Source Code for Uncertainty-Aware Multidimensional Scaling",, DaRUS, V1
This dataset contains the source code for the uncertainty-aware multidimensional scaling (UAMDS) algorithm implemented in the Java programming language. UAMDS is a nonlinear dimensionality reduction technique for sets of random vectors. The implemented UAMDS model allows to proje...
Jul 11, 2022 - SFB-TRR 161 A08 "A Learning-Based Research Methodology for Visualization"
Angerbauer, Katrin; Rodrigues, Nils; Cutura, Rene; Öney, Seyda; Pathmanathan, Nelusa; Morariu, Cristina; Weiskopf, Daniel; Sedlmair, Michael, 2022, "Supplemental Material for the paper : Accessibility for Color Vision Deficiencies: Challenges and Findings of a Large Scale Study on Paper Figures",, DaRUS, V1, UNF:6:uNArOgq9AXAmdvLcE/mMVA== [fileUNF]
Study data and supplemental material for the paper- Accessibility for Color Vision Deficiencies: Challenges and Findings of a Large Scale Study on Paper Figures presented at CHI 2022. We performed a large scale data study on the color vision deficiency (CVDs) accessibility of pap...
Jun 30, 2022 - SFB-TRR 161 A03 "Quantification of Visual Analytics Transformations and Mappings"
Dennig, Frederik L., 2022, "Replication Data for: "ParSetgnostics: Quality Metrics for Parallel Sets"",, DaRUS, V1, UNF:6:mmqXqGYXSM0L6g/xQCjGUg== [fileUNF]
This is the replication data for our research article "ParSetgnostics: Quality Metrics for Parallel Sets." It contains the datasets used to obtain optimized Parallel Sets visualizations. We used the following six datasets for our experiments, which we describe on a per-file basis...
Jun 21, 2022 - SFB-TRR 161 A07 "Visual Attention Modeling for Optimization of Information Visualizations"
Wang, Yao; Bulling, Andreas, 2022, "Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"",, DaRUS, V1, UNF:6:AuvgRc09o1rESd63AqlW9Q== [fileUNF]
Despite its importance for assessing the effectiveness of communicating information visually, fine-grained recallability of information visualisations has not been studied quantitatively so far. We propose a question-answering paradigm to study visualisation recallability and pre...
Jun 9, 2022 - SFB-TRR 161 B01 "Adaptive Self-Consistent Visualization"
Yan, Jia Jun; Rodrigues, Nils; Shao, Lin; Schreck, Tobias; Weiskopf, Daniel, 2022, "Sample Implementation for the Paper "Eye Gaze on Scatterplot: Concept and First Results of Recommendations for Exploration of SPLOMs Using Implicit Data Selection"",, DaRUS, V1
Java source code of proof-of-concept tool used for the paper "Eye Gaze on Scatterplot: Concept and First Results of Recommendations for Exploration of SPLOMs Using Implicit Data Selection". Code by M.Sc. student Jia Jun Yan. Supervision and concepts by Nils Rodrigues, Lin Shao, T...
May 20, 2022 - SFB-TRR 161 INF "Collaboration Infrastructure"
Garkov, Dimitar; Müller, Christoph; Klein, Karsten; Ertl, Thomas; Schreiber, Falk; Task-Force A, 2022, "Guidelines on Replication and Research Data Management",, DaRUS, V1
This document summarises guidelines for reproducibility in SFB/Transregio 161 by Task Force A (TF-A). It builds upon the data management plan (version 1.0, 2020, and focusses on three main points: Provide clear definitions of reproducibility an...
May 2, 2022 - SFB-TRR 161 C06 "User-Adaptive Mixed Reality"
Chiossi, Francesco; Villa, Steeven; Hauser, Melanie; Welsch, Robin; Chuang, Lewis, 2022, "Design of On-body Tactile Displays to Enhance Situation Awareness in Automated Vehicles",, DaRUS, V1, UNF:6:YHhX4VFGLE0o6fVxJAlldw== [fileUNF]
Fatalities with semi-automated vehicles typically occur when users are engaged in non-driving related tasks (NDRTs) that compromise their situational awareness (SA). This work developed a tactile display for on-body notification to support situational awareness, thus enabling use...
Apr 27, 2022 - SFB-TRR 161 C06 "User-Adaptive Mixed Reality"
Chiossi, Francesco; Welsch, Robin; Villa, Steeven; Chuang, Lewis; Mayer, Sven, 2022, "Virtual Reality Adaptation using Electrodermal Activity to Support User Experience",, DaRUS, V1
We report an experiment (N=18) where participants where engaged in a dual task setting in a Social VR (Virtual Reality) scenario. We present a physiologically-adaptive system that optimizes the virtual environment based on physiological arousal, i.e., electrodermal activity. We i...
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.