Is human classification a gold standard in fixation detection?
Creators
- 1. Utrecht University
- 2. Lund University
Description
This repository contains the coder settings and event-based agreement score algorithms used and developed for the article Hooge, I.T.C., Niehorster, D.C., Nyström, M., Andersson, R. & Hessels, R.S. (submitted). Is human classification a gold standard in fixation detection? When using the algorithms or coder settings in this repository in your work, please cite the Hooge et al. paper.
This repository also contains the eye-movement data used as stimuli in the Hooge et al. paper. These stimuli are a part of the infant eye-movement dataset collected by Hessels, R.S., Hooge, I.T.C., & Kemner, C. (2016). An in-depth look at saccadic search in infancy. Journal of Vision, 16(8), 10. http://doi.org/10.1167/16.8.10. Please cite this paper when using these eye-movement data.
For more information or questions, e-mail: i.hooge@uu.nl / dcnieho@gmail.com. The latest version of this repository is available from www.github.com/dcnieho/humanFixationClassification
The algorithms in this repository are licensed under the Creative Commons Attribution 4.0 (CC BY 4.0) license. The coder settings and eye-movement data used as stimuli are licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 (CC NC-BY-SA 4.0) license.
Contents:
- To explore the event based F1 and relative timing offset and difference scores, run the files F1_example.m and RTO_RTD_example.m, respectively.
- To reproduce the F1, RTO and RTD scores from Hooge et al. (submitted), run doF1_RTO_RTD_forAll.m
- To graphically explore the settings coders made, run coderSettingPlotter.m
- the coder settings are found in data/coderSettings
- the eye-movement data that were coded are found in data/ETdata
Tested on MATLAB R2012a & R2017a
Files
dcnieho/humanFixationClassification-v0.9.zip
Files
(1.9 MB)
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Additional details
Related works
- Is supplement to
- https://github.com/dcnieho/humanFixationClassification/tree/v0.9 (URL)