Behavioural Anomaly Detection Using Eye Movements

Joe Ninan George; Affien Panicker

Behavioural Anomaly Detection Using Eye Movements

Authors: Joe Ninan George, Affien Panicker

Unique Paper ID: 154241
Volume: 8
Issue: 7
PageNo: 104-108

Keywords: eye gaze eye movements Neuro-Linguistic Programming convolutional neural network

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.

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Cite This Article

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

Behavioural Anomaly Detection Using Eye Movements

Available:https://ijirt.org/Article?manuscript=154241

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Journal no 47859

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