Inverse Eye Tracking – Inferring Eye Movements from Keypress Data
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URL
Journal Title
Journal ISSN
Volume Title
School of Science |
Master's thesis
Authors
Date
2024-12-27
Department
Major/Subject
Human-Computer Interaction
Mcode
Degree programme
Master's Programme in Computer, Communication and Information Sciences
Language
en
Pages
40
Series
Abstract
We propose a model that predicts where users direct their gaze during interactions using only keypress data. Starting from a log of keypresses, the model generates a scanpath that details the user’s eye movements over time as they type. This model serves as a substitute for human data in scenarios where collecting eye-tracking data is costly or impractical. Our approach is built on three key insights: first, we design an inference architecture that captures individual user characteristics as a low-dimensional parameter vector; second, we introduce a novel loss function to align inferred eye movements with the timing of keypresses; third, we adopt a hybrid training strategy combining human data with synthetically generated data. This method is applicable to interactive systems equipped with predictive models of user behavior. In our evaluation, focused on the demanding task of touchscreen typing, the model demonstrated high accuracy in replicating real eye movements.Description
Supervisor
Oulasvirta, AnttiKeywords
gaze movement, touchscreen typing, amortized inference, eye-hand coordination, visual attention, computational modeling
Other note
Attachment notes
Description:
The videos for Individual-level analysis
Attachments:
supplementary_videos.zip