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Development and Calibration of an Eye-Tracking Fixation Identification Algorithm for Immersive Virtual Reality
Jose Llanes-Jurado1, Javier Marín-Morales1, Jaime Guixeres1
1Instituto de Investigación e Innovación en Bioingeniería (i3B), Universitat Politècnica de València, 46022 Valencia, Spain.
Sensors (Basel, Switzerland)
|September 5, 2020
Summary
This study developed a new dispersion-threshold algorithm for identifying eye movement fixations in head-mounted display eye-tracking. Optimal parameters were found to improve accuracy in virtual reality environments.
Area of Science:
- Human-Computer Interaction
- Computer Vision
- Neuroscience
Background:
- Fixation identification is crucial for analyzing gaze data.
- Existing algorithms' thresholds impact sensitivity.
- Adapting algorithms for head-mounted display (HMD) eye-tracking in virtual reality (VR) needs validation.
Purpose of the Study:
- Develop and validate a dispersion-threshold algorithm for HMD eye-tracking.
- Calibrate algorithm thresholds for unrestricted head movement in VR.
- Provide guidelines for calibrating fixation identification algorithms.
Main Methods:
- Developed a dispersion-threshold algorithm for eye-tracking data from an HMD.
- Proposed rules-based criteria to calibrate thresholds using fixation features.
- Evaluated algorithm performance with varying distance-dispersion and time window parameters.
Main Results:
- Identified an acceptable range for distance-dispersion thresholds (1-1.6°) and time windows (0.25-0.4 s).
- Determined the optimum parameters to be 1° for distance-dispersion and 0.25 s for time window.
- Demonstrated the algorithm's applicability to HMD-integrated eye-tracking data.
Conclusions:
- The developed dispersion-threshold algorithm is suitable for eye-tracking in HMDs within VR.
- Established optimal parameters and guidelines for calibrating fixation identification.
- This work facilitates future research using HMD eye-tracking in immersive environments.
