Eye-Tracking Feature Extraction for Biometric Machine Learning.

Journal: Frontiers in neurorobotics
Published Date:

Abstract

CONTEXT: Eye tracking is a technology to measure and determine the eye movements and eye positions of an individual. The eye data can be collected and recorded using an eye tracker. Eye-tracking data offer unprecedented insights into human actions and environments, digitizing how people communicate with computers, and providing novel opportunities to conduct passive biometric-based classification such as emotion prediction. The objective of this article is to review what specific machine learning features can be obtained from eye-tracking data for the classification task.

Authors

  • Jia Zheng Lim
    Evolutionary Computing Laboratory, Faculty of Computing and Informatics, Universiti Malaysia Sabah, Kota Kinabalu, Malaysia.
  • James Mountstephens
    Faculty of Computing and Informatics, Universiti Malaysia Sabah, Kota Kinabalu, Malaysia.
  • Jason Teo
    Faculty of Computing and Informatics, Universiti Malaysia Sabah, Kota Kinabalu, Malaysia.

Keywords

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