eyetracking-benchmarking

Analyzing experimental data comparing the performance of professional eyetrackers and webcam-based eyetrackers.

Authors

Publication Name: WIP Journal: WIP DOI: WIP

• Manuel García-Romero
• Antonio Martínez-Rojas
• Andrés Jiménez Ramírez
• José González Enríquez

The data is located in the tests folder after the execution is done.

To execute this, you can create a virtual environment:

Create a virtual environment in the current folder:

python -m venv .venv

3. Activate the virtual environment:
   • On Windows:

.venv\Scripts\activate

- On macOS/Linux:

source .venv/bin/activate

4. Make sure the virtual environment is activated. You should see the name of the virtual environment in the terminal prompt.

5. Select the Python interpreter of the virtual environment in Visual Studio Code:

   • Open the command palette and run the command Python: Select Interpreter.

Run the following command to install the required packages:

pip install -r requirements.txt

Running the Project

To run the project, execute the run.py script:

python run.py

Project Structure

• configuration/: Contains JSON configuration files for determined scenarios.
• metrics.py: Contains functions for processing and analyzing metrics.
• results.py: Handles the results of the analysis.
• run.py: Main script to execute the project.
• settings.py: Configuration settings for the project.
• tests/: Contains test data and the results of the execution.

License

This research was supported by the EQUAVEL project PID2022-137646OB-C31, funded by MICIU/AEI/10.13039/501100011033 and by FEDER, UE; the DISCOVERY project (2021/C005/00148631), funded by Unión Europea NextGeneration EU and “Plan de Recuperación, Transformación y Resiliencia” of the Ministry of Economic and Digital Transformation; and the grant FPU20/05984 funded by MICIU/AEI/10.13039/501100011033 and by FSE+.