Combining Implicit and Explicit Feature Extraction for Eye Tracking: Attention Classification Using a Heterogeneous Input

Combining Implicit and Explicit Feature Extraction for Eye Tracking: Attention Classification Using a Heterogeneous Input

Statistical measurements of eye movement-specific properties, such as fixations, saccades, blinks, or pupil dilation, are frequently utilized as input features for machine learning algorithms applied to eye tracking recordings. These characteristics are intended to be interpretable aspects of eye ga...

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Bibliographic Details
Main Authors: Lisa-Marie Vortmann, Felix Putze
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Sensors
Subjects:
eye tracking
attention
convolutional neural network
feature extraction
Markov transition fields
Gramian angular fields
Online Access:https://www.mdpi.com/1424-8220/21/24/8205

Internet

https://www.mdpi.com/1424-8220/21/24/8205

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