AEye - Artificial Intelligence for Eye Tracking Data: Deep Learning Methods for the Automated Analysis of Cognitive Processes.
The way we move our eyes is very informative about the (often unconscious) processes that unfold in our minds. Research from cognitive psychology and psycholinguistics has shown that eye movements not only reflect temporary psychological conditions of an individual such as mental fatigue, drowsiness, or the level of concentration, but also higher-level cognitive processes involved in the comprehension and production of language.
We are an interdisciplinary research group with backgrounds in Computer Science, Mathematics, Linguistics, and Cognitive Science.
Our goal is to develop machine learning methods for the analysis of eye tracking data in order to make inferences or predictions about the cognitive processes and psychological states of an individual. We are developing end-to-end-trainable deep learning architectures that can process the signal recorded from a video-based eye-tracking device. The application areas of our methods range from the eye tracking-based diagnosis of developmental language disorders (dyslexia and Specific Language Impairment SLI), adaptive e-learning (e.g., the automated assessment of reading comprehension, foreign language skills, mental fatigue or distraction), driver monitoring (e.g., detection of drowsiness or alcoholization) to biometric user identification.