Smooth pursuit detection in binocular eye-tracking data with automatic video-based performance evaluation
Författare
Summary, in English
An increasing number of researchers record binocular eye-tracking signals from participants viewing moving stimuli, but the majority of event-detection algorithms are monocular and do not consider smooth pursuit movements. The purposes of the present study are to develop an algorithm that discriminates between fixations and smooth pursuit movements in binocular eye-tracking signals and to evaluate its performance using an automated video-based strategy. The proposed algorithm uses a clustering approach that takes both spatial and temporal aspects of the binocular eyetracking signal into account, and is evaluated using a novel video-based evaluation strategy based on automatically detected moving objects in the video stimuli. The binocular algorithm detects 98% of fixations in image stimuli compared to 95% when only one eye is used, while for video stimuli, both the binocular and monocular algorithms detect around 40% of smooth pursuit movements. The present article shows that using binocular information for discrimination of fixations and smooth pursuit movements is advantageous in static stimuli, without impairing the algorithm's ability to detect smooth pursuit movements in video and movingdot stimuli. With an automated evaluation strategy, time-consuming manual annotations are avoided and a larger amount of data can be used in the evaluation process.
Avdelning/ar
Publiceringsår
2016
Språk
Engelska
Publikation/Tidskrift/Serie
Journal of Vision
Volym
16
Issue
15
Dokumenttyp
Artikel i tidskrift
Förlag
Association for Research in Vision and Ophthalmology Inc.
Ämne
- Medical Engineering
Nyckelord
- Eye tracking
- Signal processing
- Smooth pursuit
Status
Published
Forskningsgrupp
- Mathematical Imaging Group
ISBN/ISSN/Övrigt
- ISSN: 1534-7362