In this thesis, you will implement a calibration-free authentication method using a remote eye tracker. It is similar to the pattern lock in Android, but instead of using touch input, you will leverage the gaze data provided by a remote eye tracker.

Contact: omair_shahzad.bhatti@dfki.de

Reading material:

Yasmeen Abdrabou, Ken Pfeuffer, Mohamed Khamis, and Florian Alt. 2020. GazeLockPatterns: Comparing Authentication Using Gaze and Touch for Entering Lock Patterns. In ACM Symposium on Eye Tracking Research and Applications (ETRA ’20 Short Papers). Association for Computing Machinery, New York, NY, USA, Article 29, 1–6. DOI:https://doi.org/10.1145/3379156.3391371

Omair Shahzad Bhatti, Michael Barz, and Daniel Sonntag. 2021. EyeLogin – Calibration-free Authentication Method for Public Displays Using Eye Gaze. ACM Symposium on Eye Tracking Research and Applications. Association for Computing Machinery, New York, NY, USA, Article 14, 1–7. DOI:https://doi.org/10.1145/3448018.3458001