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Sebastian Mittelstädt Ehemaliges Mitglied

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LS Datenanalyse und Visualisierung Wiss. Mitarbeiter
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Forschungsinteressen

Information Visualization makes use of the human visual system to comprehend huge amounts of data and to facilitate understanding of both large-scale and small-scale features. Our cognition processes enable us to perceive even low emergent properties in large data sets that were not anticipated. However, our visual system can be biased in several ways, which is harmful for our hypothesis forming. On the signal processing levels we are biased by, for example, color constancy and brightness effects, which let us perceive color differently as it really is. These effects could have huge impact on the analysis since several visualization techniques use color to express information.

The main goal of my thesis is to compensate for physiological bias in information visualization but also to use perceptual effects to boost information in visualizations. Further, I apply these novel techniques in different application domains such as Securtity Applications & Decision Making, Cyber Physical Infrastructures or Medical Data analysis.