Dillon J Lohr
Oleg Komogortsev
ABSTRACT
This paper introduces a novel eye movement dataset collected in virtual reality (VR) that contains both 2D and 3D eye movement data from over 400 subjects. We establish that this dataset is suitable for biometric studies by evaluating it with both statistical and machine learning–based approaches. For comparison, we also include results from an existing, similarly constructed dataset.
- Lee Friedman, Mark S. Nixon, and Oleg V. Komogortsev. 2017. Method to assess the temporal persistence of potential biometric features: Application to oculomotor, gait, face and brain structure databases. PLoS ONE 12, 6 (jun 2017), e0178501. https://doi.org/10.1371/journal.pone.0178501Google Scholar
Cross Ref
- Lee Friedman, Ioannis Rigas, Evgeny Abdulin, and Oleg V. Komogortsev. 2018. A novel evaluation of two related and two independent algorithms for eye movement classification during reading. Behavior Research Methods 50, 4 (aug 2018), 1374–1397. https://doi.org/10.3758/s13428-018-1050-7Google ScholarCross Ref
- Anjith George and Aurobinda Routray. 2016. A score level fusion method for eye movement biometrics. Pattern Recognition Letters 82 (oct 2016), 207–215. https://doi.org/10.1016/j.patrec.2015.11.020 arxiv:1601.03333Google Scholar
- Dillon Lohr, Samuel-Hunter Berndt, and Oleg Komogortsev. 2018. An implementation of eye movement-driven biometrics in virtual reality. In Eye Tracking Research and Applications Symposium (ETRA). https://doi.org/10.1145/3204493.3208333Google ScholarDigital Library
- Dillon J. Lohr, Lee Friedman, and Oleg V. Komogortsev. 2019. Evaluating the data quality of eye tracking signals from a virtual reality system: Case study using SMI’s eye-tracking HTC Vive. arxiv:1912.02083Google Scholar
- Christopher W. Tyler, Anas M. Elsaid, Lora T. Likova, Navdeep Gill, and Spero C. Nicholas. 2012. Analysis of human vergence dynamics. Journal of Vision 12, 11 (oct 2012), 21–21. https://doi.org/10.1167/12.11.21Google ScholarCross Ref
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