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A field test of computer-vision-based gaze estimation in psychology

Valtakari, Niilo V ; Hessels, Roy S ; Niehorster, Diederick C LU orcid ; Viktorsson, Charlotte ; Nyström, Pär ; Falck-Ytter, Terje ; Kemner, Chantal and Hooge, Ignace T C LU (2023) In Behavior Research Methods
Abstract

Computer-vision-based gaze estimation refers to techniques that estimate gaze direction directly from video recordings of the eyes or face without the need for an eye tracker. Although many such methods exist, their validation is often found in the technical literature (e.g., computer science conference papers). We aimed to (1) identify which computer-vision-based gaze estimation methods are usable by the average researcher in fields such as psychology or education, and (2) evaluate these methods. We searched for methods that do not require calibration and have clear documentation. Two toolkits, OpenFace and OpenGaze, were found to fulfill these criteria. First, we present an experiment where adult participants fixated on nine stimulus... (More)

Computer-vision-based gaze estimation refers to techniques that estimate gaze direction directly from video recordings of the eyes or face without the need for an eye tracker. Although many such methods exist, their validation is often found in the technical literature (e.g., computer science conference papers). We aimed to (1) identify which computer-vision-based gaze estimation methods are usable by the average researcher in fields such as psychology or education, and (2) evaluate these methods. We searched for methods that do not require calibration and have clear documentation. Two toolkits, OpenFace and OpenGaze, were found to fulfill these criteria. First, we present an experiment where adult participants fixated on nine stimulus points on a computer screen. We filmed their face with a camera and processed the recorded videos with OpenFace and OpenGaze. We conclude that OpenGaze is accurate and precise enough to be used in screen-based experiments with stimuli separated by at least 11 degrees of gaze angle. OpenFace was not sufficiently accurate for such situations but can potentially be used in sparser environments. We then examined whether OpenFace could be used with horizontally separated stimuli in a sparse environment with infant participants. We compared dwell measures based on OpenFace estimates to the same measures based on manual coding. We conclude that OpenFace gaze estimates may potentially be used with measures such as relative total dwell time to sparse, horizontally separated areas of interest, but should not be used to draw conclusions about measures such as dwell duration.

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author
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organization
publishing date
type
Contribution to journal
publication status
epub
subject
keywords
eye tracking, gaze estimation, computer vision, data quality
in
Behavior Research Methods
publisher
Springer
external identifiers
  • pmid:37101100
  • scopus:85153611350
ISSN
1554-3528
DOI
10.3758/s13428-023-02125-1
language
English
LU publication?
yes
additional info
© 2023. The Author(s).
id
78901393-1f2f-46b0-8f68-5f0ccc656f33
date added to LUP
2023-04-28 12:36:08
date last changed
2024-06-15 02:19:27
@article{78901393-1f2f-46b0-8f68-5f0ccc656f33,
  abstract     = {{<p>Computer-vision-based gaze estimation refers to techniques that estimate gaze direction directly from video recordings of the eyes or face without the need for an eye tracker. Although many such methods exist, their validation is often found in the technical literature (e.g., computer science conference papers). We aimed to (1) identify which computer-vision-based gaze estimation methods are usable by the average researcher in fields such as psychology or education, and (2) evaluate these methods. We searched for methods that do not require calibration and have clear documentation. Two toolkits, OpenFace and OpenGaze, were found to fulfill these criteria. First, we present an experiment where adult participants fixated on nine stimulus points on a computer screen. We filmed their face with a camera and processed the recorded videos with OpenFace and OpenGaze. We conclude that OpenGaze is accurate and precise enough to be used in screen-based experiments with stimuli separated by at least 11 degrees of gaze angle. OpenFace was not sufficiently accurate for such situations but can potentially be used in sparser environments. We then examined whether OpenFace could be used with horizontally separated stimuli in a sparse environment with infant participants. We compared dwell measures based on OpenFace estimates to the same measures based on manual coding. We conclude that OpenFace gaze estimates may potentially be used with measures such as relative total dwell time to sparse, horizontally separated areas of interest, but should not be used to draw conclusions about measures such as dwell duration.</p>}},
  author       = {{Valtakari, Niilo V and Hessels, Roy S and Niehorster, Diederick C and Viktorsson, Charlotte and Nyström, Pär and Falck-Ytter, Terje and Kemner, Chantal and Hooge, Ignace T C}},
  issn         = {{1554-3528}},
  keywords     = {{eye tracking; gaze estimation; computer vision; data quality}},
  language     = {{eng}},
  month        = {{04}},
  publisher    = {{Springer}},
  series       = {{Behavior Research Methods}},
  title        = {{A field test of computer-vision-based gaze estimation in psychology}},
  url          = {{http://dx.doi.org/10.3758/s13428-023-02125-1}},
  doi          = {{10.3758/s13428-023-02125-1}},
  year         = {{2023}},
}