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Hand-eye coordination-based implicit re-calibration method for gaze tracking on ultrasound machines: a statistical approach

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

Eye gaze tracking is proving to be beneficial in many biomedical applications. The performance of systems based on eye gaze tracking is very much dependent on how accurate their calibration is. It has been reported that the gaze tracking accuracy deteriorates cumulatively and significantly with usage time. This impedes the wide use of gaze tracking in user interfaces.

Methods

Explicit re-calibration, typically requiring the user’s active attention, is time-consuming and can interfere with the user’s main activity. Therefore, we propose an implicit re-calibration method, which can rectify the deterioration of the gaze tracking accuracy without bringing about the user’s deliberate attention. We make use of hand-eye coordination, with the reasonable assumption that the eye gaze follows the pointer during a selection task, to acquire additional calibration points during normal usage of a gaze-contingent system. We construct a statistical model for the calibration and the hand-eye coordination and apply the Gaussian process regression framework to perform the re-calibration.

Results

To validate our model and method, we performed a user study on ultrasonography tasks on a gaze-contingent interface for ultrasound machines. Results suggest that our method can rectify the tracking accuracy deterioration for \(75\%\) of all cases where deterioration occurs in our user study. With another benchmark dataset, our method can redress tracking accuracy to a level comparable to the initial calibration in more than \(80\%\) of the cases.

Conclusions

Our implicit re-calibration method is a practical and convenient fix for tracking accuracy deterioration in gaze-contingent user interfaces, and in particular for gaze-contingent ultrasound machines.

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Acknowledgements

This work was supported by an NSERC Strategic Project Grant and by infrastructure purchased with Grants from CFI, involving Canadian federal and British Columbia Provincial support. The authors would like to deliver appreciations to all participants in our user study, as well as to authors of [17] who shared their experimental data publicly.

Funding

This work was supported by an NSERC Strategic Project Grant and by infrastructure purchased with grants from CFI, involving Canadian federal and British Columbia Provincial support.

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Authors and Affiliations

  1. School of Biomedical Engineering, University of British Columbia, Vancouver, Canada

    Hongzhi Zhu

  2. Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, Canada

    Robert N. Rohling & Septimiu E. Salcudean

  3. Department of Mechanical Engineering, University of British Columbia, Vancouver, Canada

    Robert N. Rohling

Authors
  1. Hongzhi Zhu
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  2. Robert N. Rohling
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  3. Septimiu E. Salcudean
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Corresponding author

Correspondence to Hongzhi Zhu.

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Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

The user study performed in our research is approved by the Behavioural Research Ethics Board at the University of British Columbia.

Informed consent

Informed consent was obtained from all individual participants included in the study.

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Zhu, H., Rohling, R.N. & Salcudean, S.E. Hand-eye coordination-based implicit re-calibration method for gaze tracking on ultrasound machines: a statistical approach. Int J CARS 15, 837–845 (2020). https://doi.org/10.1007/s11548-020-02143-w

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  • DOI: https://doi.org/10.1007/s11548-020-02143-w

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