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Related Experiment Video

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A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers
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Gaze tracking system for user wearing glasses.

Su Yeong Gwon1, Chul Woo Cho2, Hyeon Chang Lee3

  • 1Division of Electronics and Electrical Engineering, Dongguk University, 26 Pil-dong 3-ga, Jung-gu, Seoul 100-715, Korea. gwonsuyeong@dongguk.edu.

Sensors (Basel, Switzerland)
|January 30, 2014
PubMed
Summary
This summary is machine-generated.

This study introduces a novel gaze tracking method for eyeglass wearers, significantly reducing errors caused by reflections. The system accurately detects gaze direction even with glasses, improving precision in eye-tracking applications.

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Area of Science:

  • Computer Vision
  • Human-Computer Interaction
  • Biomedical Engineering

Background:

  • Gaze tracking systems struggle with eyeglass reflections, leading to pupil and corneal specular reflection (SR) detection errors.
  • Accurate gaze estimation relies on precise pupil center and SR localization.

Purpose of the Study:

  • To develop a robust gaze tracking method for users wearing eyeglasses.
  • To overcome limitations of conventional systems caused by reflections from eyeglass lenses.

Main Methods:

  • A novel illuminator control system with four corner-positioned lights.
  • Automatic detection of eyeglasses by analyzing white pixels under low camera exposure.
  • Sequential illuminator activation to minimize eyeglass reflections and enable accurate SR and pupil center detection.
  • Estimation of the fourth corneal SR position based on a parallelogram formed by three visible SRs to calculate gaze position.

Main Results:

  • Achieved an average gaze detection error of approximately 0.70° across 20 participants.
  • Demonstrated a processing time of 63.72 ms per frame, ensuring real-time performance.
  • Successfully mitigated noise from eyeglass reflections, allowing for accurate feature localization.

Conclusions:

  • The proposed method effectively addresses gaze tracking challenges for eyeglass wearers.
  • This technique enhances the accuracy and reliability of gaze detection in real-world scenarios.
  • The system offers a practical solution for improved human-computer interaction and research involving eye-tracking.