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High-Accuracy Gaze Estimation for Interpolation-Based Eye-Tracking Methods

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High-Accuracy Gaze Estimation for Interpolation-Based Eye-Tracking Methods. / Batista Narcizo, Fabricio; dos Santos, Fernando Eustáquio Dantas; Hansen, Dan Witzner.

In: Vision, Vol. 5, No. 3, 15.09.2021, p. 1.

Research output: Journal Article or Conference Article in JournalJournal articleResearchpeer-review

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@article{e64c8d92752640109aeb8bda444fe325,
title = "High-Accuracy Gaze Estimation for Interpolation-Based Eye-Tracking Methods",
abstract = "This study investigates the influence of the eye-camera location associated with the accuracy and precision of interpolation-based eye-tracking methods. Several factors can negatively influence gaze estimation methods when building a commercial or off-the-shelf eye tracker device, including the eye-camera location in uncalibrated setups. Our experiments show that the eye-camera location combined with the non-coplanarity of the eye plane deforms the eye feature distribution when the camera is far from the eye's optical axis. This paper proposes geometric transformation methods to reshape the eye feature distribution based on the virtual alignment of the eye-camera in the center of the eye's optical axis. The data analysis uses eye-tracking data from a simulated environment and an experiment with 83 volunteer participants (55 males and 28 females). We evaluate the improvements achieved with the proposed methods using Gaussian analysis, which defines a range for high-accuracy gaze estimation between −0.5º and +0.5º. Compared to traditional polynomial-based and homography-based gaze estimation methods, the proposed methods increase the number of gaze estimations in the high-accuracy range.",
keywords = "high-accuracy gaze estimation, uncalibrated setup, gaze-mapping calibration, eye-tracking, eye tracker",
author = "{Batista Narcizo}, Fabricio and {dos Santos}, {Fernando Eust{\'a}quio Dantas} and Hansen, {Dan Witzner}",
year = "2021",
month = sep,
day = "15",
doi = "10.3390/vision5030041",
language = "English",
volume = "5",
pages = "1",
journal = "Vision",
issn = "2411-5150",
publisher = "MDPI",
number = "3",

}

RIS

TY - JOUR

T1 - High-Accuracy Gaze Estimation for Interpolation-Based Eye-Tracking Methods

AU - Batista Narcizo, Fabricio

AU - dos Santos, Fernando Eustáquio Dantas

AU - Hansen, Dan Witzner

PY - 2021/9/15

Y1 - 2021/9/15

N2 - This study investigates the influence of the eye-camera location associated with the accuracy and precision of interpolation-based eye-tracking methods. Several factors can negatively influence gaze estimation methods when building a commercial or off-the-shelf eye tracker device, including the eye-camera location in uncalibrated setups. Our experiments show that the eye-camera location combined with the non-coplanarity of the eye plane deforms the eye feature distribution when the camera is far from the eye's optical axis. This paper proposes geometric transformation methods to reshape the eye feature distribution based on the virtual alignment of the eye-camera in the center of the eye's optical axis. The data analysis uses eye-tracking data from a simulated environment and an experiment with 83 volunteer participants (55 males and 28 females). We evaluate the improvements achieved with the proposed methods using Gaussian analysis, which defines a range for high-accuracy gaze estimation between −0.5º and +0.5º. Compared to traditional polynomial-based and homography-based gaze estimation methods, the proposed methods increase the number of gaze estimations in the high-accuracy range.

AB - This study investigates the influence of the eye-camera location associated with the accuracy and precision of interpolation-based eye-tracking methods. Several factors can negatively influence gaze estimation methods when building a commercial or off-the-shelf eye tracker device, including the eye-camera location in uncalibrated setups. Our experiments show that the eye-camera location combined with the non-coplanarity of the eye plane deforms the eye feature distribution when the camera is far from the eye's optical axis. This paper proposes geometric transformation methods to reshape the eye feature distribution based on the virtual alignment of the eye-camera in the center of the eye's optical axis. The data analysis uses eye-tracking data from a simulated environment and an experiment with 83 volunteer participants (55 males and 28 females). We evaluate the improvements achieved with the proposed methods using Gaussian analysis, which defines a range for high-accuracy gaze estimation between −0.5º and +0.5º. Compared to traditional polynomial-based and homography-based gaze estimation methods, the proposed methods increase the number of gaze estimations in the high-accuracy range.

KW - high-accuracy gaze estimation

KW - uncalibrated setup

KW - gaze-mapping calibration

KW - eye-tracking

KW - eye tracker

UR - https://github.com/fabricionarcizo/eyeinfo

UR - https://github.com/fabricionarcizo/et_simul/tree/mdpi-vision-2021

UR - https://github.com/fabricionarcizo/eye-tracking-data

U2 - 10.3390/vision5030041

DO - 10.3390/vision5030041

M3 - Journal article

VL - 5

SP - 1

JO - Vision

JF - Vision

SN - 2411-5150

IS - 3

ER -

ID: 86176303