I had the chance to interview Prof. Grinstein after his talk ‘Visual Analytics: A Modern View of its Future and Research Opportunities’ at the University of Konstanz in June 2017, when he visited Prof. Daniel A. Keim and his project team within the SFB-TRR 161. In my interview he was answering questions like “Why is research in the field of computer science, data visualization and visual analytics so important?”, “What are the major risks of visualization and visual analytics in the future?”, “What do we have to teach our children to make them fit for the future world?”, or “What challenges does Georges Grinstein still have?”
Ich habe mein BOGY an der Universität Konstanz im Bereich „Computer Vision and Image Analysis“ absolviert. Meine BOGY Woche begann am 24. März um 10 Uhr. Alle BOGYs trafen sich zusammen mit ihren jeweiligen Tutoren und lernten sich kennen. Nachdem uns grob unterschiedliche Aufgaben der einzelnen Bereiche vorgestellt wurden, welche sehr interessant waren, folgten wir unserem jeweiligen Tutor an unseren Arbeitsplatz.
From April 24th to 28th, I took part in a BOGY-Internship at SFB-TRR 161. I was assigned to Mr. Kölbl’s team at the University of Konstanz who is working on an implementation of a model checker for creating so-called fault trees which are supposed to help spotting potential errors in safety-critical systems.
Today’s briefing started at 9:30 a.m. on Monday, March 24th, 2017 and I didn‘t know what to expect. We had been attending some impressive presentations about multiple projects at SFB-TRR-161 and now I really wanted to know more about the entire work.
Humans rely on eye sight and the processing of the resulting information in more everyday tasks than we realize. We are able to solve moderately difficult quadratic formulas in our head when taking information about a flying ball and aiming to hit it with a baseball bet at incredible speeds. We are able to use visual information about dozens of cars to navigate when driving a car in unknown streets. Our eyes calibrate to the lighting conditions allowing us to navigate broad daylight just as well as dimly lit rooms. Beyond that, we can use information about depth of field, color, tint, and sharpness. In fact, it is often said that over 50% of the cortex, the surface of the brain, is involved in vision processing tasks. This makes vision one of the most relied upon sense. Consequently, understanding what drives our eye movements may be a key to understanding how the brain as a whole works.
As I have been interested in computers since my childhood and spend some of my free time with programming, I decided to attend an internship in the field of computer science. The choice fell to the Visualization Research Center (VISUS), as I hoped to gain as much experience as possible in the three areas of work, research and student life.
Kuno Kurzhals is a visualization scientist at the Visualization Research Center of the University of Stuttgart (VISUS) with special focus on video visualization and evaluation methods in combination with eye tracking. His research is associated with the SFB-TRR 161 where scientists whant to establish quantification as a key ingredient of visual computing research. In this video interview he talks about the challenges and aims of his activities and explains some of his visualization results.
Franz Hahn is a PhD student in the Multimedia Signal Processing Group of Prof. Dietmar Saupe at the University of Konstanz. During his project activities in the SFB-TRR 161 he is concerned with the topic of image and video quality assessment. Using Eye Tracking he aims to develop a predictive model that improves the quality of images by keeping the data size the same.
“What we aim for in the end is some sort of mechanism, that tells us, whether the users understood, what they were looking at.”
Jakob Karolus is a researcher at the Institute for Visualization and Interactive Systems at the University of Stuttgart working in the field of Human-Computer Interaction. Within the project SFB-TRR 161 “Quantitative Methods for Visual Computing” he wants to find out how different visualizations influence the eyemovement patterns of people.
Smartphones take our holiday pictures, send a reminder of upcoming appointments, and help us find the way to a meeting point. Cars are learning to see, computer generated images entertain us in cinemas and video games, and we view new products online in 3D before purchase.