research-article

Gazture: Design and Implementation of a Gaze based Gesture Control System on Tablets

Authors:

Jiliang WangAuthors Info & Claims

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Volume 1, Issue 3

Article No.: 74, Pages 1 - 17

https://doi.org/10.1145/3130939

Published: 11 September 2017 Publication History

Abstract

We present Gazture, a light-weight gaze based real-time gesture control system on commercial tablets. Unlike existing approaches that require dedicated hardware (e.g., high resolution camera), high computation overhead (powerful CPU) or specific user behavior (keeping head steady), Gazture provides gesture recognition based on easy-to-control user gaze input with a small overhead. To achieve this goal, Gazture incorporates a two-layer structure: The first layer focuses on real-time gaze estimation with acceptable tracking accuracy while incurring a small overhead. The second layer implements a robust gesture recognition algorithm while compensating gaze estimation error. To address user posture change while using mobile device, we design a online transfer function based method to convert current eye features into corresponding eye features in reference posture, which then facilitates efficient gaze position estimation. We implement Gazture on Lenovo Tab3 8 Plus tablet with Android 6.0.1, and evaluate its performance in different scenarios. The evaluation results show that Gazture can achieve a high accuracy in gesture recognition while incurring a low overhead.

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Cited By

Namnakani OSinrattanavong PAbdrabou YBulling AAlt FKhamis M(2023)GazeCast: Using Mobile Devices to Allow Gaze-based Interaction on Public DisplaysProceedings of the 2023 Symposium on Eye Tracking Research and Applications10.1145/3588015.3589663(1-8)Online publication date: 30-May-2023
https://dl.acm.org/doi/10.1145/3588015.3589663
Li JRay SRajanna VHammond T(2022)Evaluating the Performance of Machine Learning Algorithms in Gaze Gesture Recognition SystemsIEEE Access10.1109/ACCESS.2021.313615310(1020-1035)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2021.3136153
Shen LChen YLiu J(2022)Gaze-Assisted Viewport Control for 360° Video on SmartphoneJournal of Computer Science and Technology10.1007/s11390-022-2037-537:4(906-918)Online publication date: 30-Jul-2022
https://doi.org/10.1007/s11390-022-2037-5
Show More Cited By

Index Terms

Gazture: Design and Implementation of a Gaze based Gesture Control System on Tablets
1. Human-centered computing
  1. Ubiquitous and mobile computing
    1. Ubiquitous and mobile computing design and evaluation methods

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cover image Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Volume 1, Issue 3

September 2017

2023 pages

EISSN:2474-9567

DOI:10.1145/3139486

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Copyright © 2017 ACM.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 11 September 2017

Accepted: 01 July 2017

Revised: 01 May 2017

Received: 01 February 2017

Published in IMWUT Volume 1, Issue 3

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Cited By

Namnakani OSinrattanavong PAbdrabou YBulling AAlt FKhamis M(2023)GazeCast: Using Mobile Devices to Allow Gaze-based Interaction on Public DisplaysProceedings of the 2023 Symposium on Eye Tracking Research and Applications10.1145/3588015.3589663(1-8)Online publication date: 30-May-2023
https://dl.acm.org/doi/10.1145/3588015.3589663
Li JRay SRajanna VHammond T(2022)Evaluating the Performance of Machine Learning Algorithms in Gaze Gesture Recognition SystemsIEEE Access10.1109/ACCESS.2021.313615310(1020-1035)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2021.3136153
Shen LChen YLiu J(2022)Gaze-Assisted Viewport Control for 360° Video on SmartphoneJournal of Computer Science and Technology10.1007/s11390-022-2037-537:4(906-918)Online publication date: 30-Jul-2022
https://doi.org/10.1007/s11390-022-2037-5
Shi LCopot CVanlanduit S(2021)Gaze Gesture Recognition by Graph Convolutional NetworksFrontiers in Robotics and AI10.3389/frobt.2021.7099528Online publication date: 5-Aug-2021
https://doi.org/10.3389/frobt.2021.709952
Shen LChen YLiu J(2021)Energy-Efficient Interactive 360° Video Streaming with Real-Time Gaze Tracking on Mobile Devices2021 IEEE 18th International Conference on Mobile Ad Hoc and Smart Systems (MASS)10.1109/MASS52906.2021.00040(243-251)Online publication date: Oct-2021
https://doi.org/10.1109/MASS52906.2021.00040
Hassib MAbdelmoteleb HKhamis M(2020)Are my Apps Peeking? Comparing Nudging Mechanisms to Raise Awareness of Access to Mobile Front-facing CameraProceedings of the 19th International Conference on Mobile and Ubiquitous Multimedia10.1145/3428361.3428384(186-190)Online publication date: 22-Nov-2020
https://dl.acm.org/doi/10.1145/3428361.3428384
Fuhl W(2020)From perception to action using observed actions to learn gesturesUser Modeling and User-Adapted Interaction10.1007/s11257-020-09275-3Online publication date: 24-Aug-2020
https://doi.org/10.1007/s11257-020-09275-3
Ma XJiang CLuo YZhao QJin MHe YLiu YXing GHe YPicco G(2019)Poster: A Calibration-free Gaze based Mobile Gesture Control SystemProceedings of the 2019 International Conference on Embedded Wireless Systems and Networks10.5555/3324320.3324354(222-223)Online publication date: 25-Feb-2019
https://dl.acm.org/doi/10.5555/3324320.3324354
Nguyen VRupavatharam SLiu LHoward RGruteser MGanti RJiang XPicco GZhou X(2019)HandSenseProceedings of the 17th Conference on Embedded Networked Sensor Systems10.1145/3356250.3360040(285-297)Online publication date: 10-Nov-2019
https://dl.acm.org/doi/10.1145/3356250.3360040
Truong HZhang SMuncuk UNguyen PBui NNguyen ALv QChowdhury KDinh TVu T(2018)CapBandProceedings of the 16th ACM Conference on Embedded Networked Sensor Systems10.1145/3274783.3274854(54-67)Online publication date: 4-Nov-2018
https://dl.acm.org/doi/10.1145/3274783.3274854
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