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Get a grip : Slippage-robust and glint-free gaze estimation for real-time pervasive head-mounted eye tracking

Santini, Thiago; Niehorster, Diederick C. LU and Kasneci, Enkelejda (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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Please use this url to cite or link to this publication:
author
organization
publishing date
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
editor
Spencer, Stephen N. and
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
2019-08-28 04:57:42
@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},
  editor       = {Spencer, Stephen N.},
  isbn         = {9781450367097},
  keyword      = {Calibration,Drift,Embedded,Eye tracking,Gaze estimation,Open source,Pervasive,Pupil tracking,Real-time,Slippage},
  language     = {eng},
  location     = {Denver, United States},
  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},
  year         = {2019},
}