abstract

Hybrid model and appearance based eye tracking with kinect

Authors:

Kang Wang,

Qiang JiAuthors Info & Claims

ETRA '16: Proceedings of the Ninth Biennial ACM Symposium on Eye Tracking Research & Applications

Pages 331 - 332

https://doi.org/10.1145/2857491.2888591

Published: 14 March 2016 Publication History

Get Access

Abstract

Existing gaze estimation methods rely mainly on 3D eye model or 2D eye appearance. While both methods have validated their effectiveness in various fields and applications, they are still limited in practice, such as portable and non-intrusive system and robust eye gaze tracking in different environments. To this end, we investigate on combining eye model with eye appearance to perform gaze estimation and eye gaze tracking. Specifically, unlike traditional 3D model based methods which rely on cornea reflections, we plan to retrieve 3D information from depth sensor (Eg, Kinect). Kinect integrates camera sensor and IR illuminations into one single device, thus enable more flexible system settings. We further propose to utilize appearance information to help the basic model based methods. Appearance information can help better detection of gaze related features (Eg, pupil center). Plus, eye model and eye appearance can benefit each other to enable robust and accurate gaze estimation.

References

[1]

BioID. Bioid database https://www.bioid.com/about/bioid-face-database.

Google Scholar

[2]

Funes Mora, K. A., and Odobez, J. 2014. Geometric generative gaze estimation (g3e) for remote rgb-d cameras. CVPR.

Digital Library

Google Scholar

[3]

Krizhevsky, A., Sutskever, I., and Hinton, G. E. 2012. Imagenet classification with deep convolutional neural networks. In Advances in neural information processing systems.

Google Scholar

[4]

Song, F., Tan, X., Chen, S., and Zhou, Z.-H. 2013. A literature survey on robust and efficient eye localization in real-life scenarios. Pattern Recognition.

Digital Library

Google Scholar

[5]

Sun, L., Song, M., Liu, Z., and Sun, M. 2014. Real-time gaze estimation with online calibration. IEEE Multimedia and Expo.

Google Scholar

[6]

Xiong, X., and De la Torre, F. 2013. Supervised descent method and its application to face alignment. CVPR.

Digital Library

Google Scholar

[7]

Y. Sugano, Y. Matsushita, and Y. Sato. 2013. Appearance-based gaze estimation using visual saliency. IEEE Trans. Pattern Analysis and Machine Intelligence.

Digital Library

Google Scholar

Cited By

View all

Zhu LChen JYang HZhou XGao QLoureiro RGao SZhao H(2024)Wearable Near-Eye Tracking Technologies for Health: A ReviewBioengineering10.3390/bioengineering1107073811:7(738)Online publication date: 22-Jul-2024
https://doi.org/10.3390/bioengineering11070738
Ghosh SDhall AHayat MKnibbe JJi Q(2024)Automatic Gaze Analysis: A Survey of Deep Learning Based ApproachesIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2023.332133746:1(61-84)Online publication date: Jan-2024
https://doi.org/10.1109/TPAMI.2023.3321337
Xu XChen JLi CFu CYang LYan YLyu Z(2024)Robust Gaze Point Estimation for Metaverse With Common Mode Features Suppression NetworkIEEE Transactions on Consumer Electronics10.1109/TCE.2024.335119070:1(2090-2098)Online publication date: Feb-2024
https://doi.org/10.1109/TCE.2024.3351190
Show More Cited By

Index Terms

Hybrid model and appearance based eye tracking with kinect
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
  2. Machine learning

Recommendations

Automatic acquisition of a 3D eye model for a wearable first-person vision device
ETRA '12: Proceedings of the Symposium on Eye Tracking Research and Applications

A wearable gaze tracking device can work with users in daily-life. For long time of use, a non-active method that does not employ an infrared illumination system is desirable from safety standpoint. It is well known that the eye model constraints ...
A fast approach to refraction-aware eye-model fitting and gaze prediction
ETRA '19: Proceedings of the 11th ACM Symposium on Eye Tracking Research & Applications

By temporally integrating information about pupil contours extracted from eye images, model-based methods for glint-free gaze estimation can mitigate pupil detection noise. However, current approaches require time-consuming iterative solving of a ...
Analysis of eye tracking movements using FIR median hybrid filters
ETRA '00: Proceedings of the 2000 symposium on Eye tracking research & applications

This paper presents an approach of using FIR Median Hybrid Filters for analysis of eye tracking movements. The proposed filter can remove the eye blink artifact from the eye movement signal. The background of the project is described first. The whole ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

ETRA '16: Proceedings of the Ninth Biennial ACM Symposium on Eye Tracking Research & Applications

March 2016

378 pages

ISBN:9781450341257

DOI:10.1145/2857491

Conference Chairs:
Pernilla Qvarfordt
FX Palo Alto Laboratory
,
Dan Witzner Hansen
IT University of Copenhagen, Denmark

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 14 March 2016

Check for updates

Author Tags

Qualifiers

Abstract

Conference

ETRA '16

Sponsor:

ETRA '16: 2016 Symposium on Eye Tracking Research and Applications

March 14 - 17, 2016

South Carolina, Charleston

Acceptance Rates

Overall Acceptance Rate 69 of 137 submissions, 50%

Upcoming Conference

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

6
Total Citations
View Citations
284
Total Downloads

Downloads (Last 12 months)2
Downloads (Last 6 weeks)1

Reflects downloads up to 10 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Zhu LChen JYang HZhou XGao QLoureiro RGao SZhao H(2024)Wearable Near-Eye Tracking Technologies for Health: A ReviewBioengineering10.3390/bioengineering1107073811:7(738)Online publication date: 22-Jul-2024
https://doi.org/10.3390/bioengineering11070738
Ghosh SDhall AHayat MKnibbe JJi Q(2024)Automatic Gaze Analysis: A Survey of Deep Learning Based ApproachesIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2023.332133746:1(61-84)Online publication date: Jan-2024
https://doi.org/10.1109/TPAMI.2023.3321337
Xu XChen JLi CFu CYang LYan YLyu Z(2024)Robust Gaze Point Estimation for Metaverse With Common Mode Features Suppression NetworkIEEE Transactions on Consumer Electronics10.1109/TCE.2024.335119070:1(2090-2098)Online publication date: Feb-2024
https://doi.org/10.1109/TCE.2024.3351190
Wang KZhao RSu HJi Q(2019)Generalizing Eye Tracking With Bayesian Adversarial Learning2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR.2019.01218(11899-11908)Online publication date: Jun-2019
https://doi.org/10.1109/CVPR.2019.01218
Wang KSu HJi Q(2019)Neuro-Inspired Eye Tracking With Eye Movement Dynamics2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR.2019.01006(9823-9832)Online publication date: Jun-2019
https://doi.org/10.1109/CVPR.2019.01006
Brousseau BRose JEizenman M(2018)Accurate Model-Based Point of Gaze Estimation on Mobile DevicesVision10.3390/vision20300352:3(35)Online publication date: 24-Aug-2018
https://doi.org/10.3390/vision2030035

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

Automatic acquisition of a 3D eye model for a wearable first-person vision device

A fast approach to refraction-aware eye-model fitting and gaze prediction

Analysis of eye tracking movements using FIR median hybrid filters