One algorithm to rule them all? : An evaluation and discussion of ten eye movement event-detection algorithms
Andersson, Richard LU ; Larsson, Linnéa LU ; Holmqvist, Kenneth LU ; Stridh, Martin LU and Nyström, Marcus LU
(2017)
In Behavior Research Methods
49(2).
p.616-637
- Abstract
- Almost all eye-movement researchers use algorithms to parse raw data and detect distinct types of eye movement events, such as fixations, saccades, and pursuit, and then base their results on these. Surprisingly, these algorithms are rarely evaluated. We evaluated the classifications of ten eye-movement event detection algorithms, on data from an SMI HiSpeed 1250 system, and compared them to manual ratings of two human experts. The evaluation focused on fixations, saccades, and post-saccadic oscillations. The evaluation used both event duration parameters, and sample-by-sample comparisons to rank the algorithms. The resulting event durations varied substantially as a function of what algorithm was used. This evaluation differed from... (More)
- Almost all eye-movement researchers use algorithms to parse raw data and detect distinct types of eye movement events, such as fixations, saccades, and pursuit, and then base their results on these. Surprisingly, these algorithms are rarely evaluated. We evaluated the classifications of ten eye-movement event detection algorithms, on data from an SMI HiSpeed 1250 system, and compared them to manual ratings of two human experts. The evaluation focused on fixations, saccades, and post-saccadic oscillations. The evaluation used both event duration parameters, and sample-by-sample comparisons to rank the algorithms. The resulting event durations varied substantially as a function of what algorithm was used. This evaluation differed from previous evaluations by considering a relatively large set of algorithms, multiple events, and data from both static and dynamic stimuli. The main conclusion is that current detectors of only fixations and saccades work reasonably well for static stimuli, but barely better than chance for dynamic stimuli. Differing results across evaluation methods make it difficult to select one winner for fixation detection. For saccade detection, however, the algorithm by Larsson, Nyström and Stridh (IEEE Transaction on Biomedical Engineering, 60(9):2484–2493,2013) outperforms all algorithms in data from both static and dynamic stimuli. The data also show how improperly selected algorithms applied to dynamic data misestimate fixation and saccade properties. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/784a92cf-a4aa-452f-9acd-faafd94366cd
- author
- Andersson, Richard
LU
; Larsson, Linnéa
LU
; Holmqvist, Kenneth
LU
; Stridh, Martin
LU
and Nyström, Marcus
LU
- organization
- publishing date
- 2017
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- ögonrörelsemätning, Eye-tracking, Inter-rater reliability, Parsing
- in
- Behavior Research Methods
- volume
- 49
- issue
- 2
- pages
- 616 - 637
- publisher
- Springer
- external identifiers
-
- scopus:84969836647
- pmid:27193160
- wos:000400391800016
- ISSN
- 1554-3528
- DOI
- 10.3758/s13428-016-0738-9
- language
- English
- LU publication?
- yes
- id
- 784a92cf-a4aa-452f-9acd-faafd94366cd
- date added to LUP
- 2016-04-20 14:21:57
- date last changed
- 2023-02-07 18:50:59
@article{784a92cf-a4aa-452f-9acd-faafd94366cd,
abstract = {{Almost all eye-movement researchers use algorithms to parse raw data and detect distinct types of eye movement events, such as fixations, saccades, and pursuit, and then base their results on these. Surprisingly, these algorithms are rarely evaluated. We evaluated the classifications of ten eye-movement event detection algorithms, on data from an SMI HiSpeed 1250 system, and compared them to manual ratings of two human experts. The evaluation focused on fixations, saccades, and post-saccadic oscillations. The evaluation used both event duration parameters, and sample-by-sample comparisons to rank the algorithms. The resulting event durations varied substantially as a function of what algorithm was used. This evaluation differed from previous evaluations by considering a relatively large set of algorithms, multiple events, and data from both static and dynamic stimuli. The main conclusion is that current detectors of only fixations and saccades work reasonably well for static stimuli, but barely better than chance for dynamic stimuli. Differing results across evaluation methods make it difficult to select one winner for fixation detection. For saccade detection, however, the algorithm by Larsson, Nyström and Stridh (IEEE Transaction on Biomedical Engineering, 60(9):2484–2493,2013) outperforms all algorithms in data from both static and dynamic stimuli. The data also show how improperly selected algorithms applied to dynamic data misestimate fixation and saccade properties.}},
author = {{Andersson, Richard and Larsson, Linnéa and Holmqvist, Kenneth and Stridh, Martin and Nyström, Marcus}},
issn = {{1554-3528}},
keywords = {{ögonrörelsemätning; Eye-tracking; Inter-rater reliability; Parsing}},
language = {{eng}},
number = {{2}},
pages = {{616--637}},
publisher = {{Springer}},
series = {{Behavior Research Methods}},
title = {{One algorithm to rule them all? : An evaluation and discussion of ten eye movement event-detection algorithms}},
url = {{https://lup.lub.lu.se/search/files/16640393/2016_Andersson_Algorithms_eval_accepted_version.pdf}},
doi = {{10.3758/s13428-016-0738-9}},
volume = {{49}},
year = {{2017}},
}