Collaborative Research Center
SFB-TRR 161
Quantitative Methods for Visual Computing
We are living in a data society in which data is generated at amazing speed; individuals, companies, organizations, and governments are on the brink of being drawn into a massive deluge of data. The great challenge is to extract the relevant information from vast amounts of data and communicate it effectively.
Typical scenarios include decision and policy making for urban and environmental planning or understanding relationships and dependencies in complex networks, e.g., social networks or networks from the field of bioinformatics. These scenarios are not only of interest to specialized experts; in fact, there is a trend toward including the broad public, which requires the information to be presented in a reliable, faithful, and easy-to-understand fashion.
Visual computing can play a key role in extracting and presenting the relevant information.
In visual computing research the aspect of quantification is often neglected. The SFB-TRR 161 seeks to close this gap.
The long-term goal is to strengthen the research field by establishing the paradigm of quantitative science in visual computing.
News
December 2024
Andreas Bulling Appointed as Henriette Herz Scout
Fellowship of the Alexander von Humboldt Foundation provides unique funding opportunity on the postdoctoral level
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November
Progressive Data Analysis: New Book Co-Edited by Michael Sedlmair
Book introduces a new computational paradigm and outlines a roadmap for further research
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Michael Sedlmair Elected as Member of the IEEE VIS Steering Committee
VIS Steering Committee provides scientific and organizational oversight of IEEE VIS conference
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SFB-TRR 161 Events
Jan 13th, 2025, 4 pm - 6 pm
University of Stuttgart
Lecture | Eye Tracking in the Context of Human Augmentation
Held by:
Kenan Bektas, Universität St. Gallen
Abstract:
Visual perception plays a vital role in our daily decision-making activities. However, recent technologies provide us with access to exponentially growing amount of information and challenge the limits of our comprehension. Thus, we need solutions that augment our capabilities, thereby helping us to overcome such limitations. In this talk, I will give an overview of selected work where we addressed some of the perceptual and cognitive limitations with the help of eye tracking solutions. Specifically, I will answer questions such as: How can we use foveated gaze-contingent displays as an aid in visual search tasks? Can we use eye tracking to supplement manual annotation tasks? How can we use a gaze-enabled augmented reality headset for the externalization of human memory? How does gaze-sharing help in collaborative activities as a non-verbal communication cue? How can we predict human activities from their eye movements and facilitate intuitive interactions with everyday objects?
Bio:
Kenan Bektas is a postdoc researcher and lecturer in the Interaction- and Communication-based Systems Group of the Institute of Computer Science, The University of St. Gallen, Switzerland and also works as a senior researcher in the Cantonal Hospital St. Gallen (Ostschweizer Schulungs- und Trainingszentrum). He received his Ph.D. degree from the University of Zurich, Faculty of Science, in 2018. Kenan’s research interests comprise human visual perception, embodied human-computer interaction, human augmentation, and pervasive applications of eye tracking. He coauthored multiple publications in venues such as the ACM ETRA, CHI, IMWUT, and the IEEE TVCG.
Location:
University of Stuttgart, Visualization Research Center (VISUS), Room: 00.012University of Konstanz, Room: ZT 702
The lecture will be transmitted to the University of Konstanz, Room: ZT 702
All doctoral researchers are asked to take part in the events of the lecture series.
Jan 20th, 2025, 4 pm - 6 pm
LMU Munich
Lecture | tbd
Held by:
Location:
LMU Munich, Room: tbd
The lecture will be transmitted to the University of Stuttgart, Visualization Research Center (VISUS), Room: 00.012. and to the University of Konstanz, Room: ZT 702.
All doctoral researchers are asked to take part in the events of the lecture series.
Jan 24th, 2025, 2.15 pm -3.15 pm
University of Stuttgart
Talk | Learning with Music Signals: Technology Meets Education
Held by:
Meinard Müller, International Audio Laboratories Erlangen
Abstract:
Music information retrieval (MIR) is a dynamic research field at the intersection of engineering and the humanities, connecting disciplines such as signal processing, machine learning, musicology, and digital humanities. In this presentation, we explore learning in MIR from both technological and educational perspectives, using music as a tangible application domain. Our focus is on integrating deep learning with traditional engineering approaches to develop explainable hybrid models. By collaborating with domain experts and utilizing specialized music corpora, we demonstrate how computational tools can advance musicological research while uncovering data biases and confounding factors in modern technologies. Furthermore, we emphasize how music can facilitate interactive learning in technical disciplines, promoting innovation at the crossroads of technology and education.
Bio:
Meinard Müller received the Diploma degree (1997) in mathematics and the Ph.D. degree (2001) in computer science from the University of Bonn, Germany. After his postdoctoral studies (2001-2003) in Japan and his habilitation (2003-2007) in multimedia retrieval in Bonn, he worked as a senior researcher at Saarland University and the Max-Planck Institut für Informatik (2007-2012). Since 2012, he has held a professorship for Semantic Audio Signal Processing at the International Audio Laboratories Erlangen, a joint institute of the Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and the Fraunhofer Institute for Integrated Circuits IIS. His research interests include music processing, music information retrieval, audio signal processing, and motion processing. He wrote a monograph titled "Information Retrieval for Music and Motion" (Springer 2007) and a textbook titled "Fundamentals of Music Processing" (Springer 2015). In 2020, he was elevated to IEEE Fellow for contributions to music signal processing.
Location:
University of Stuttgart, VISUS, Room 00.012
The talk will be available via WebEx.
Jan 27th, 2025, 4 pm - 6 pm
LMU Munich
Lecture | tbd
Held by:
Felix Putze, Universität Bremen
Location:
LMU Munich, Room: tbd
The lecture will be transmitted to the University of Stuttgart, Visualization Research Center (VISUS), Room: 00.012. and to the University of Konstanz, Room: ZT 702.
All doctoral researchers are asked to take part in the events of the lecture series.
Jan 30th, 2025, 10.30 am - 12 pm
University of Stuttgart
Talk | tbd
Held by:
Michael Burch, FH Graubünden, CH
Location:
University of Stuttgart, VISUS, Room 00.012
The talk will be available via WebEx.
Feb 3rd, 2025, 4 pm - 6 pm
University of Stuttgart
Lecture | tbd
Held by:
Jürgen Bernard, Universität Zürich
Location:
University of Stuttgart, Visualization Research Center (VISUS), Room: 00.012University of Konstanz, Room: ZT 702
The lecture will be transmitted to the University of Konstanz, Room: ZT 702
All doctoral researchers are asked to take part in the events of the lecture series.
May 26th - 28th, 2025, full days
Humboldt Haus, Aichberg bei Lindau am Bodensee
Doctoral Retreat of the SFB-TRR 161
Oct 6th - 7th, 2025, full days
Internal Status Seminar of the SFB-TRR 161
Further Information & Resources
YouTube
The SFB-TRR 161 produces videos to give insights into the projects and the ongoing research. Please visit our YouTube Channel.
Graduate School
PhD students of the projects at the Universities of Stuttgart and Konstanz learn and do research together on their way to their doctoral degree in visual computing.
Visual Computing Blog
The scientists of the SFB-TRR 161 as well as guest authors blog about their activities in computer graphics, visualization, computer vision, augmented reality, human-computer interaction, and psychology.
Partners of the SFB-TRR 161
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© SFB-TRR 161 | Quantitative Methods for Visual Computing | 2019.