User Authentication by Eye Movement Features Employing SVM and XGBoost Classifiers
Author:
Affiliation:
1. Department of Multimedia Systems, Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology, Gdańsk, Poland
Funder
Polish National Centre for Research and Development (NCBR) funded the Research Project entitled: “BIOPUAP—a biometric cloud authentication system” from the European Regional Development Fund
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/10005208/10231085.pdf?arnumber=10231085
Reference43 articles.
1. An Approach to Biometric Identification by Using Low-Frequency Eye Tracker
2. Eye Know You Too: Toward Viable End-to-End Eye Movement Biometrics for User Authentication
3. Gaze trajectory as a biometric modality;deravi;Proc Int Conf Bio-Inspired Syst Signal Process,2011
4. Eye-Tracking Feature Extraction for Biometric Machine Learning
5. 28 Blinks Later
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