A Multimodal Eye Movement Dataset and a Multimodal Eye Movement Segmentation Analysis
This provides a resource for developers of real-time systems and algorithms to select optimal data sources for eye movement applications, though it is incremental as it focuses on dataset creation and analysis without introducing new methods.
The authors tackled the problem of eye movement classification by presenting a new annotated dataset of over 800,000 gaze points from 19 subjects in real-world and simulator car rides, analyzing multiple data sources like eyelid closure and pupil center to evaluate their goodness of fit for classification.
We present a new dataset with annotated eye movements. The dataset consists of over 800,000 gaze points recorded during a car ride in the real world and in the simulator. In total, the eye movements of 19 subjects were annotated. In this dataset there are several data sources such as the eyelid closure, the pupil center, the optical vector, and a vector into the pupil center starting from the center of the eye corners. These different data sources are analyzed and evaluated individually as well as in combination with respect to their goodness of fit for eye movement classification. These results will help developers of real-time systems and algorithms to find the best data sources for their application. Also, new algorithms can be trained and evaluated on this data set. The data and the Matlab code can be downloaded here https://atreus.informatik.uni-tuebingen.de/seafile/d/8e2ab8c3fdd444e1a135/?p=%2FA%20Multimodal%20Eye%20Movement%20Dataset%20and%20...&mode=list