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.
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.
Our last post was about presentations at IEEE VIS 2016 in Baltimore. Apart from the already mentioned publications, there were more presentations by SFB-TRR 161 scientists at the conference.
This year, the IEEE VIS conference took part in Baltimore, Maryland which is also dubbed ‘Charm City’ by the locals. The conference was held in the Baltimore Convention Center, at the Hilton Hotel. The location is situated not far from the Inner Harbor of Baltimore, a very nice and scenic place. The conference consists of three tracks (InfoVis, SciVis & VAST). Additionally, there are many workshops and tutorials.
This summer, I spent three months at the Ilab at the University of Calgary. My supervisor Sheelagh Carpendale is head of the InnoVis group which is part of the Ilab. I had the opportunity to visit the Ilab through the MIN Program: Mentoring International for Female Natural Scientists at the University Konstanz and which was funded by the Transregional Collaborative Research Center (SFR-TRR) 161. During my time, I worked with five great researchers evaluating a website developed and designed by them.
This summer was a bit different to me than for the rest of my colleagues at Visual Analytics and Imaging (VAI) Lab Stony Brook University and SUNY Korea, as I spent it in Visualization Research Center of the University of Stuttgart (VISUS) for a short research trip. I got this opportunity through the PhD fellowship program, offered by the Transregional Collaborative Research Center (SFR-TRR) 161. I carried out my research in Stuttgart, with many Ph.D.’s and Post-Doc’s at single place and which was definitely a learning experience for me. The whole experience was very different for me but indeed fruitful.
Nowadays a big vision of the automotive industry is autonomous driving. Since Google’s introduction of autonomously driving cars, car manufacturers, their suppliers, but also IT companies and the scientific community are excited about the upcoming revolution of transportation. The biggest advantages of autonomous driving are a higher driving comfort, and assumed the driving systems work reliably, a better driving safety. But there are many issues that have to be resolved until autonomous driving can be fully realized.
Humans are the end users of visual media. Therefore, in order to develop an effective quantitative assessment of visual computing quality, one must take into account how humans perceive visual quality. For example, in image compression, an adaptive bitrate allocation that favors the image foreground can be expected to increase the visual quality of decoded images.