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.
Individuals, companies, organizations, and governments deal with information and data on a daily basis, in professional and private contexts. One of our great challenges is to extract the relevant information from ever increasing amounts of data produced by sensors, simulation, or as output from databases and information systems. Visual presentation is one of the key elements in extracting and communicating information. With this Visual Computing BLOG, we want to discuss fundamental questions of visual computing and the latest research developments.