ARETT

ARETT acquires and analyzes eye-tracking data from the Microsoft HoloLens 2 within Unity 3D to quantify gaze accuracy and precision for augmented reality research.


Key Features:

  • Integration with Unity 3D: Leverages Unity 3D for embedding eye-tracking routines and scripting support.
  • Microsoft HoloLens 2 eye tracker: Uses the built-in eye tracker of the Microsoft HoloLens 2 for gaze data acquisition in AR scenarios.
  • Data acquisition scripts: Provides scripts for acquisition of eye-tracking data from the HoloLens 2.
  • R package for analysis: Includes an R package for comprehensive eye-tracking data analysis.
  • Spatial accuracy and precision evaluation: Implements evaluation of spatial accuracy and precision of gaze estimates under varying conditions.
  • Validated performance: Demonstrated angular accuracy of 0.83 degrees and precision of 0.27 degrees at rest in a 21-participant study.

Scientific Applications:

  • Cognitive and educational research: Supports studies in cognitive and educational sciences using gaze metrics in AR.
  • Visual attention studies: Enables investigation of visual attention in virtual and augmented reality environments.
  • Gaze-based interaction and rendering optimization: Supports development and assessment of gaze-driven interaction techniques and rendering optimization in AR.
  • User behavior and content delivery: Facilitates research to understand user behavior and optimize AR content delivery.
  • Interactive system development: Aids development of interactive AR systems that leverage eye-tracking data.

Methodology:

Provides scripts for eye-tracking data acquisition, an R package for eye-tracking data analysis, and procedures to evaluate spatial accuracy and precision of gaze estimates.

Topics

Details

License:
MIT
Tool Type:
workflow
Programming Languages:
C#, JavaScript, R
Added:
6/14/2021
Last Updated:
8/13/2021

Operations

Publications

Kapp S, Barz M, Mukhametov S, Sonntag D, Kuhn J. ARETT: Augmented Reality Eye Tracking Toolkit for Head Mounted Displays. Sensors. 2021;21(6):2234. doi:10.3390/s21062234. PMID:33806863. PMCID:PMC8004990.

PMID: 33806863
PMCID: PMC8004990
Funding: - Bundesministerium für Bildung und Forschung: 01JD1811B, 01JD1811C

Links