Get a grip : Slippage-robust and glint-free gaze estimation for real-time pervasive head-mounted eye tracking
(2019) 11th ACM Symposium on Eye Tracking Research and Applications, ETRA 2019- Abstract
A key assumption conventionally made by flexible head-mounted eye-tracking systems is often invalid: The eye center does not remain stationary w.r.t. the eye camera due to slippage. For instance, eye-tracker slippage might happen due to head acceleration or explicit adjustments by the user. As a result, gaze estimation accuracy can be significantly reduced. In this work, we propose Grip, a novel gaze estimation method capable of instantaneously compensating for eye-tracker slippage without additional hardware requirements such as glints or stereo eye camera setups. Grip was evaluated using previously collected data from a large scale unconstrained pervasive eye-tracking study. Our results indicate significant slippage compensation... (More)
A key assumption conventionally made by flexible head-mounted eye-tracking systems is often invalid: The eye center does not remain stationary w.r.t. the eye camera due to slippage. For instance, eye-tracker slippage might happen due to head acceleration or explicit adjustments by the user. As a result, gaze estimation accuracy can be significantly reduced. In this work, we propose Grip, a novel gaze estimation method capable of instantaneously compensating for eye-tracker slippage without additional hardware requirements such as glints or stereo eye camera setups. Grip was evaluated using previously collected data from a large scale unconstrained pervasive eye-tracking study. Our results indicate significant slippage compensation potential, decreasing average participant median angular offset by more than 43% w.r.t. a non-slippage-robust gaze estimation method. A reference implementation of Grip was integrated into EyeRecToo, an open-source hardware-agnostic eye-tracking software, thus making it readily accessible for multiple eye trackers (Available at: www.ti.uni-tuebingen.de/perception).
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- author
- Santini, Thiago ; Niehorster, Diederick C. LU and Kasneci, Enkelejda
- organization
- publishing date
- 2019-06-25
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Calibration, Drift, Embedded, Eye tracking, Gaze estimation, Open source, Pervasive, Pupil tracking, Real-time, Slippage
- host publication
- Proceedings - ETRA 2019 : 2019 ACM Symposium On Eye Tracking Research and Applications - 2019 ACM Symposium On Eye Tracking Research and Applications
- editor
- Spencer, Stephen N.
- article number
- 17
- publisher
- Association for Computing Machinery (ACM)
- conference name
- 11th ACM Symposium on Eye Tracking Research and Applications, ETRA 2019
- conference location
- Denver, United States
- conference dates
- 2019-06-25 - 2019-06-28
- external identifiers
-
- scopus:85069454357
- ISBN
- 9781450367097
- DOI
- 10.1145/3314111.3319835
- language
- English
- LU publication?
- yes
- id
- 63f2a7f8-f896-4867-a320-c2916183dddf
- date added to LUP
- 2019-08-02 18:49:57
- date last changed
- 2022-04-26 03:26:08
@inproceedings{63f2a7f8-f896-4867-a320-c2916183dddf, abstract = {{<p>A key assumption conventionally made by flexible head-mounted eye-tracking systems is often invalid: The eye center does not remain stationary w.r.t. the eye camera due to slippage. For instance, eye-tracker slippage might happen due to head acceleration or explicit adjustments by the user. As a result, gaze estimation accuracy can be significantly reduced. In this work, we propose Grip, a novel gaze estimation method capable of instantaneously compensating for eye-tracker slippage without additional hardware requirements such as glints or stereo eye camera setups. Grip was evaluated using previously collected data from a large scale unconstrained pervasive eye-tracking study. Our results indicate significant slippage compensation potential, decreasing average participant median angular offset by more than 43% w.r.t. a non-slippage-robust gaze estimation method. A reference implementation of Grip was integrated into EyeRecToo, an open-source hardware-agnostic eye-tracking software, thus making it readily accessible for multiple eye trackers (Available at: www.ti.uni-tuebingen.de/perception).</p>}}, author = {{Santini, Thiago and Niehorster, Diederick C. and Kasneci, Enkelejda}}, booktitle = {{Proceedings - ETRA 2019 : 2019 ACM Symposium On Eye Tracking Research and Applications}}, editor = {{Spencer, Stephen N.}}, isbn = {{9781450367097}}, keywords = {{Calibration; Drift; Embedded; Eye tracking; Gaze estimation; Open source; Pervasive; Pupil tracking; Real-time; Slippage}}, language = {{eng}}, month = {{06}}, publisher = {{Association for Computing Machinery (ACM)}}, title = {{Get a grip : Slippage-robust and glint-free gaze estimation for real-time pervasive head-mounted eye tracking}}, url = {{http://dx.doi.org/10.1145/3314111.3319835}}, doi = {{10.1145/3314111.3319835}}, year = {{2019}}, }