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Related Experiment Video

Updated: Jul 9, 2025

Gaze in Action: Head-mounted Eye Tracking of Children's Dynamic Visual Attention During Naturalistic Behavior
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GaVe: A Webcam-Based Gaze Vending Interface Using One-Point Calibration.

Zhe Zeng1, Sai Liu1, Hao Cheng2

  • 1Technical University of Berlin, Germany.

Journal of Eye Movement Research
|November 29, 2023
PubMed
Summary
This summary is machine-generated.

Gaze input using the GazeVending (GaVe) interface allows users to control displays with their eyes. This eye-tracking system demonstrated efficient item selection, with users choosing items in under 7 seconds.

Keywords:
Human-computer interactiondwell timeeye movementeye trackinggazegaze interactiontouchlessusability

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Area of Science:

  • Human-Computer Interaction
  • Computer Vision
  • Usability Engineering

Background:

  • Contact-free interaction is crucial for advanced human-machine systems.
  • Gaze input offers a promising avenue for intuitive control.
  • Existing gaze interfaces often require specialized hardware or complex calibration.

Purpose of the Study:

  • To introduce the GazeVending (GaVe) interface for eye-controlled interaction.
  • To evaluate the usability and performance of GaVe using a user study.
  • To establish design guidelines for hierarchical gaze-based interfaces.

Main Methods:

  • Developed GaVe, a hierarchical interface controlled by eye-gaze dwell time.
  • Utilized a standard webcam for gaze tracking with minimal calibration.
  • Conducted a user study (N=22) to determine optimal dwell times and interaction distances.
  • Collected data on user perception, error rates, and task completion times.

Main Results:

  • All participants successfully learned and interacted with the GaVe interface.
  • Average task completion time for selecting an item from 12 options was 6.76 seconds.
  • Users reported positive perceptions of the system's ease of use and efficiency.

Conclusions:

  • The GazeVending interface provides an effective and user-friendly method for gaze-based control.
  • Hierarchical design and dwell-time selection are viable for managing large item sets.
  • GaVe demonstrates the potential of webcam-based eye-tracking for accessible human-machine interaction.