https://github.com/tjmahr/eyetracking-from-scratch

https://github.com/tjmahr/eyetracking-from-scratch

Last synced: 3 months ago
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• Host: GitHub
• URL: https://github.com/tjmahr/eyetracking-from-scratch
• Owner: tjmahr
• License: gpl-3.0
• Created: 2020-01-29T19:34:56.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2020-01-29T19:56:21.000Z (over 5 years ago)
• Last Synced: 2025-02-24T13:56:36.250Z (3 months ago)
• Size: 15.6 KB
• Stars: 0
• Watchers: 5
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# eyetracking-from-scratch

main steps:

- collecting data (your job)

- reading in data

- time-locking

- mapping to AOIs

- interpolating/deblinking

- classifying trials by location at a given time

- this is the dataset! store it.

- aggregating looks

- modeling: gca, splines, nonlinear regression

- miscellany

reading in data

- let's assume bare minimum

  - one row per time sample with gaze coordinates for each eye

  - eyelink might not give this? (never used it)

- what do we have

  - screen proportions? pixels?

- where is the origin

  - screens put 0,0 in upper left corner because cathode ray guns. decartes put 0,0 in bottom-left

- normalize origin and pixels

- offscreen looks?

  - just set them to NA

- monocular averaging

  - eye-dentification problems

  - read the manual: do they include quality/reliability measures for each sample?

- let's make a plot

 

databasing eyetracking data

- experiment features / experiment administrations / trials / looks

- participants

- other tables to link to participants

miscellany

- visual angles, finding saccades, smoothing data

- clean reaction times are so uncommon what do they even measure

- coded videos

  - 30 frames per second

  - where is left?

- let the light in: pupillometry