This repository contains:
- Analysis pipeline for automated dynamic gaze mapping
- Code and results for accuracy and precision comparisons across two models of wearable eye-tracker
Wearable eye-trackers introduce the challenge of translating recorded gaze locations from a egocentric coordinate system (i.e. the outward facing camera on the glasses which records the participant's point-of-view) and a fixed reference stimulus in the environment. This pipeline is used to detect a specific target stimulus in the enviorment, and then transform the gaze data to be expressed relative to the target:
This pipeline currently supports the following wearable eye-trackers:
- Pupil Labs
- Tobii Pro Glasses 2
- SMI ETG 2
For more information look in: gazeMappingPipeline/gazeMappingGuide.md
We benchmarked accuracy and precision performance across 3 models of wearable eye-tracker (Pupil Labs 120 Hz Binocular, Tobii Pro Glasses 2, SMI ETG 2)
For results and stats, see: analysis/calibrationAnalyses.md