A simple way to estimate similarity between pairs of eye movement sequences

We propose a novel algorithm to estimate the similarity between a pair of eye movement sequences. The proposed algorithm relies on a straight-forward geometric representation of eye movement data. The algorithm is considerably simpler to implement and apply than existing similarity measures, and is...

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Main Authors: Sebastiaan Mathôt, Filipe Cristino, Iain D. Gilchrist, Jan Theeuwes
Format: Article
Language:English
Published: MDPI AG 2012-03-01
Series:Journal of Eye Movement Research
Subjects:
Online Access:https://bop.unibe.ch/JEMR/article/view/2326
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author Sebastiaan Mathôt
Filipe Cristino
Iain D. Gilchrist
Jan Theeuwes
author_facet Sebastiaan Mathôt
Filipe Cristino
Iain D. Gilchrist
Jan Theeuwes
author_sort Sebastiaan Mathôt
collection DOAJ
description We propose a novel algorithm to estimate the similarity between a pair of eye movement sequences. The proposed algorithm relies on a straight-forward geometric representation of eye movement data. The algorithm is considerably simpler to implement and apply than existing similarity measures, and is particularly suited for exploratory analyses. To validate the algorithm, we conducted a benchmark experiment using realistic artificial eye movement data. Based on similarity ratings obtained from the proposed algorithm, we defined two clusters in an unlabelled set of eye movement sequences. As a measure of the algorithm's sensitivity, we quantified the extent to which these data-driven clusters matched two pre-defined groups (i.e., the 'real' clusters). The same analysis was performed using two other, commonly used similarity measures. The results show that the proposed algorithm is a viable similarity measure.
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issn 1995-8692
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series Journal of Eye Movement Research
spelling doaj-art-4ea07cfd0ac247fab24d004cec6f846a2025-08-20T03:26:21ZengMDPI AGJournal of Eye Movement Research1995-86922012-03-015110.16910/jemr.5.1.4A simple way to estimate similarity between pairs of eye movement sequencesSebastiaan Mathôt0Filipe Cristino1Iain D. Gilchrist2Jan Theeuwes3Vrije Universiteit, AmsterdamBangor UniversityUniversity of BristolVrije Universiteit, AmsterdamWe propose a novel algorithm to estimate the similarity between a pair of eye movement sequences. The proposed algorithm relies on a straight-forward geometric representation of eye movement data. The algorithm is considerably simpler to implement and apply than existing similarity measures, and is particularly suited for exploratory analyses. To validate the algorithm, we conducted a benchmark experiment using realistic artificial eye movement data. Based on similarity ratings obtained from the proposed algorithm, we defined two clusters in an unlabelled set of eye movement sequences. As a measure of the algorithm's sensitivity, we quantified the extent to which these data-driven clusters matched two pre-defined groups (i.e., the 'real' clusters). The same analysis was performed using two other, commonly used similarity measures. The results show that the proposed algorithm is a viable similarity measure.https://bop.unibe.ch/JEMR/article/view/2326eye movementsdistancesimilarityscanpathsmethodology
spellingShingle Sebastiaan Mathôt
Filipe Cristino
Iain D. Gilchrist
Jan Theeuwes
A simple way to estimate similarity between pairs of eye movement sequences
Journal of Eye Movement Research
eye movements
distance
similarity
scanpaths
methodology
title A simple way to estimate similarity between pairs of eye movement sequences
title_full A simple way to estimate similarity between pairs of eye movement sequences
title_fullStr A simple way to estimate similarity between pairs of eye movement sequences
title_full_unstemmed A simple way to estimate similarity between pairs of eye movement sequences
title_short A simple way to estimate similarity between pairs of eye movement sequences
title_sort simple way to estimate similarity between pairs of eye movement sequences
topic eye movements
distance
similarity
scanpaths
methodology
url https://bop.unibe.ch/JEMR/article/view/2326
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