@inproceedings{2aaa3f10f72d479aa8e8e6c5bdbbaa6a,
title = "A Multimodal Eye Movement Dataset and a Multimodal Eye Movement Segmentation Analysis",
abstract = "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 including 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 suitability 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. Link to code and dataset https://atreus.informatik.uni-tuebingen.de/seafile/d/8e2ab8c3fdd444e1a135/?p=%2FA%20Multimodal%20Eye%20Movement%20Dataset%20and%20...mode=list",
keywords = "Classification, Data set, Driving, Eye Movements, Machine Learning, Real World, Segmentation",
author = "Wolfgang Fuhl and Enkelejda Kasneci",
note = "Publisher Copyright: {\textcopyright} 2021 ACM.; 2021 ACM Symposium on Eye Tracking Research and Applications, ETRA 2021 ; Conference date: 24-05-2021 Through 27-05-2021",
year = "2021",
month = may,
day = "25",
doi = "10.1145/3448018.3458004",
language = "English",
series = "Eye Tracking Research and Applications Symposium (ETRA)",
publisher = "Association for Computing Machinery",
editor = "Spencer, {Stephen N.}",
booktitle = "Proceedings - ETRA 2021",
}