PyEtSimul : An Open-Source Python Framework for Eye-Tracking Simulation
Salari, Mohammadhossein ; Niehorster, Diederick C. LU
; Hansen, Dan Witzner
and Bednarik, Roman
(2026)
In Proceedings of the ACM on Human-Computer Interaction
10(3).
- Abstract
- This paper presents PyEtSimul, an open-source Python-based framework for simulating video-based eye trackers by generating synthetic eye features through geometric modeling. The framework allows flexible positioning of eyes, cameras, and light sources in 3D space, with controlled variation of eye anatomical features and camera properties. PyEtSimul generalizes corneal modeling by representing the cornea as a conic surface rather than the common sphere. It also supports non-circular pupil shapes, size-dependent pupil decentration, eyelid occlusion, and camera lens distortion. It supports systematic data generation and principled comparison of gaze estimation algorithms across calibrated and uncalibrated settings. These features enable... (More)
- This paper presents PyEtSimul, an open-source Python-based framework for simulating video-based eye trackers by generating synthetic eye features through geometric modeling. The framework allows flexible positioning of eyes, cameras, and light sources in 3D space, with controlled variation of eye anatomical features and camera properties. PyEtSimul generalizes corneal modeling by representing the cornea as a conic surface rather than the common sphere. It also supports non-circular pupil shapes, size-dependent pupil decentration, eyelid occlusion, and camera lens distortion. It supports systematic data generation and principled comparison of gaze estimation algorithms across calibrated and uncalibrated settings. These features enable analyses not possible with other available simulators. PyEtSimul facilitates controlled experiments with known parameters often latent in normal settings, enabling reproducible benchmarking and systematic exploration of hardware designs. By generating fully synthetic data, PyEtSimul removes privacy concerns and the need for costly hardware, making it practical for both educational and research applications. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/eff1afa9-cb59-4fba-935e-b2c0c4c9511f
- author
- Salari, Mohammadhossein
; Niehorster, Diederick C.
LU
; Hansen, Dan Witzner
and Bednarik, Roman
- organization
- publishing date
- 2026-05-31
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Eye tracking, Gaze estimation, Optical simulation, Simulation
- in
- Proceedings of the ACM on Human-Computer Interaction
- volume
- 10
- issue
- 3
- article number
- ETRA009
- pages
- 17 pages
- publisher
- Association for Computing Machinery (ACM)
- external identifiers
-
- scopus:105040705892
- ISSN
- 2573-0142
- DOI
- 10.1145/3806023
- language
- English
- LU publication?
- yes
- id
- eff1afa9-cb59-4fba-935e-b2c0c4c9511f
- date added to LUP
- 2026-06-01 19:02:15
- date last changed
- 2026-06-30 10:52:55
@article{eff1afa9-cb59-4fba-935e-b2c0c4c9511f,
abstract = {{This paper presents PyEtSimul, an open-source Python-based framework for simulating video-based eye trackers by generating synthetic eye features through geometric modeling. The framework allows flexible positioning of eyes, cameras, and light sources in 3D space, with controlled variation of eye anatomical features and camera properties. PyEtSimul generalizes corneal modeling by representing the cornea as a conic surface rather than the common sphere. It also supports non-circular pupil shapes, size-dependent pupil decentration, eyelid occlusion, and camera lens distortion. It supports systematic data generation and principled comparison of gaze estimation algorithms across calibrated and uncalibrated settings. These features enable analyses not possible with other available simulators. PyEtSimul facilitates controlled experiments with known parameters often latent in normal settings, enabling reproducible benchmarking and systematic exploration of hardware designs. By generating fully synthetic data, PyEtSimul removes privacy concerns and the need for costly hardware, making it practical for both educational and research applications.}},
author = {{Salari, Mohammadhossein and Niehorster, Diederick C. and Hansen, Dan Witzner and Bednarik, Roman}},
issn = {{2573-0142}},
keywords = {{Eye tracking; Gaze estimation; Optical simulation; Simulation}},
language = {{eng}},
month = {{05}},
number = {{3}},
publisher = {{Association for Computing Machinery (ACM)}},
series = {{Proceedings of the ACM on Human-Computer Interaction}},
title = {{PyEtSimul : An Open-Source Python Framework for Eye-Tracking Simulation}},
url = {{http://dx.doi.org/10.1145/3806023}},
doi = {{10.1145/3806023}},
volume = {{10}},
year = {{2026}},
}