Human Computer Interaction

Human-Computer Interaction

Eye-tracking technology has found its way into many fields of research and applications, enabling sensing of the visual behavior in mobile, outdoor settings. Our vision are computing systems that sense and infer the user’s cognitive state based on eye movements and provide information for assistive technologies in many activities of everyday life.

Towards this vision, our research has focused on (i) the development of novel algorithms and tools for real-time and efficient eye tracking and data analysis and (ii) modelling user behavior based on eye movement analysis. We provide a comprehensive tool-chain of methods, starting from robust gaze estimation in natural settings through event detection to the automated analysis of visual exploration. Based on these methods, we have explored visual information processing, visual search and cognitive aspects related to vision in laboratory, virtual reality and real-world settings, such as driving or shopping.

Recent News

02.02.2021

Paper acceptance at the IEEE Conference on Virtual Reality and 3D User Interfaces 2021 (IEEE VR 2021).

The paper “Exploiting Object-of-Interest Information to Understand Attention in VR Classrooms” was accepted at the IEEE VR 2021. Details will follow.

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20.01.2021

Paper acceptance at the ACM CHI Conference on Human Factors in Computing Systems 2021 (CHI 2021).

The paper “Digital Transformations of Classrooms in Virtual Reality” was accepted at the ACM CHI 2021. Details will follow soon.

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08.07.2020

Liebherr-Elektronik GmbH funds research project at the University of Tübingen

Liebherr-Elektronik GmbH and the University of Tübingen are researching efficient machine learning methods for use in real-time critical automation tasks. The cooperation, which is funded by Liebherr-Elektronik, is headed by Prof. Dr. Enkelejda Kasneci, holder of the chair for human-machine interaction.

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