This is the readme file for the code package for the paper: 
"Consider the Head Movements! Saccade Computation in Mobile Eye-Tracking": https://doi.org/10.1145/3517031.3529624
by Negar Alinaghi (negar.alinaghi@geo.tuwien.ac.at) and Ioannis Giannopoulos (igiannopoulos@geo.tuwien.ac.at)
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* The idt.py file is computing the fixations (and saccades) based on the algorithm by Dario D. Salvucci (https://doi.org/10.1145/355017.355028)
** Input data is the gaze positions as a csv file with these columns: 
*** 'gaze_timestamp': the timestamp of the gaze position, starting at 0 (start of recording).
*** 'world_index': number of the frame on the scene camera video
*** 'confidence': a quality measure not yet (June 2022) implemented by PupilLabs and therefore contains integers equal to 0. If you don't have this column, create a column with this header and set all values equal to 0.
*** 'norm_pos_x': normalized x-position of the gaze
*** 'norm_pos_y': normalized y-position of the gaze

* The main.py uses the "fixation_... .csv" file which is the output of idt.py, as well as the corresponding video file which should be a .mp4 file (in our case with farme rate of 30). 
* The output is a csv file named "corrected_fixation_... .csv" which contains the corrected x and y coordinates of the fixations. 
* This corrected coordinates can be further used for calculating the saccade length and azimuth.

*IMPORTANT NOTE: A gaze position file as a sample (4bwCZ9awAx_unfamiliar.csv) is shared, but the video file cannot be shared due to privacy and ethics regulations.