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

24.06.2020

Paper accepted at the International Conference on Pattern Recognition 2020 (ICPR)

The paper “Fully Convolutional Neural Networks for Raw Eye Tracking Data Segmentation, Generation, and Reconstruction” was accepted at the International Conference on Pattern Recognition 2020.

Read more ...

06.06.2020

Best paper award at 2020 Eye Tracking and Reseach Applications Conference

The paper “A Min hash approach to scanpath classification” received the best paper award at 2020 Eye Tracking and Reseach Applications Conference (ETRA).

Read more ...

29.05.2020

Expertise and cognitive load article published in Plos One

Recent Publication in the Plos One Journal (May 2020)

Read more ...

All news are shown here: News page.

All News