Behavioural Anomaly Detection Using Eye Movements

  • Unique Paper ID: 154241
  • Volume: 8
  • Issue: 7
  • PageNo: 104-108
  • Abstract:
  • In a variety of human-computer interface tasks, estimating eye gaze direction is beneficial. Knowledge of the user's gaze direction can provide useful information about the user's focus. Certain eye movements, according to proponents of Neuro- Linguistic Programming (NLP), provides an educated guess about whether or not the person matches the description with the standard set of directions. Despite widespread acceptance of this concept, no previous research has been conducted to test its validity. The classification of eye gaze direction is done using a convolutional neural network.

Copyright & License

Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{154241,
        author = {Joe Ninan George and Affien Panicker},
        title = {Behavioural Anomaly Detection Using Eye Movements},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {7},
        pages = {104-108},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=154241},
        abstract = {In a variety of human-computer interface tasks, estimating eye gaze direction is beneficial. Knowledge of the user's gaze direction can provide useful information about the user's focus. Certain eye movements, according to proponents of Neuro- Linguistic Programming (NLP), provides an educated guess about whether or not the person matches the description with the standard set of directions. Despite widespread acceptance of this concept, no previous research has been conducted to test its validity. The classification of eye gaze direction is done using a convolutional neural network.},
        keywords = {eye gaze, eye movements, Neuro-Linguistic Programming, convolutional neural network},
        month = {},
        }

Cite This Article

  • ISSN: 2349-6002
  • Volume: 8
  • Issue: 7
  • PageNo: 104-108

Behavioural Anomaly Detection Using Eye Movements

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