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Identification system based on eye movements modeled as an Ornstein-Uhlenbeck process (Paper).
Install required libraries with Anaconda:
conda create --name gazeID -c conda-forge --file requirements.txtconda activate gazeID
InstallNSLR-HMM
python -m pip install git+https://gitlab.com/nslr/nslr
Extract Ornstein-Uhlenbeck features fromFIFA-DB dataset (datasets/FIFA) launching the moduleextract_OU_params.py, results will be saved infeatures/FIFA_OU_posterior_VI.
Moduleevent_kfold.py exploits SVMs for classification on the features extracted as an Ornstein-Uhlenbeck process via a Nested cross-validation procedure.
If you use this code, please cite the paper:
@article{damelio2023using,AUTHOR = {D’Amelio, Alessandro and Patania, Sabrina and Bursic, Sathya and Cuculo, Vittorio and Boccignone, Giuseppe},TITLE = {Using Gaze for Behavioural Biometrics},JOURNAL = {Sensors},VOLUME = {23},YEAR = {2023},NUMBER = {3},ARTICLE-NUMBER = {1262},URL = {https://www.mdpi.com/1424-8220/23/3/1262},ISSN = {1424-8220},DOI = {10.3390/s23031262}}@article{d2021gazing, title={Gazing at Social Interactions Between Foraging and Decision Theory}, author={D'Amelio, Alessandro and Boccignone, Giuseppe}, journal={Frontiers in neurorobotics}, volume={15}, pages={31}, year={2021}, publisher={Frontiers}}@article{boccignone2020gaze, title={On gaze deployment to audio-visual cues of social interactions}, author={Boccignone, Giuseppe and Cuculo, Vittorio and D’Amelio, Alessandro and Grossi, Giuliano and Lanzarotti, Raffaella}, journal={IEEE Access}, volume={8}, pages={161630--161654}, year={2020}, publisher={IEEE}}About
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