AIMC Topic: Eye Movements

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Deep-SAGA: a deep-learning-based system for automatic gaze annotation from eye-tracking data.

Behavior research methods
With continued advancements in portable eye-tracker technology liberating experimenters from the restraints of artificial laboratory designs, research can now collect gaze data from real-world, natural navigation. However, the field lacks a robust me...

A Driver Gaze Estimation Method Based on Deep Learning.

Sensors (Basel, Switzerland)
Car crashes are among the top ten leading causes of death; they could mainly be attributed to distracted drivers. An advanced driver-assistance technique (ADAT) is a procedure that can notify the driver about a dangerous scenario, reduce traffic cras...

iCatcher: A neural network approach for automated coding of young children's eye movements.

Infancy : the official journal of the International Society on Infant Studies
Infants' looking behaviors are often used for measuring attention, real-time processing, and learning-often using low-resolution videos. Despite the ubiquity of gaze-related methods in developmental science, current analysis techniques usually involv...

Danger, high voltage! Using EEG and EOG measurements for cognitive overload detection in a simulated industrial context.

Applied ergonomics
Industrial settings will be characterized by far-reaching production automation brought about by advancements in robotics and artificial intelligence. As a consequence, human assembly workers will need to adapt quickly to new and more complex assembl...

Viewport-Based CNN: A Multi-Task Approach for Assessing 360° Video Quality.

IEEE transactions on pattern analysis and machine intelligence
For 360° video, the existing visual quality assessment (VQA) approaches are designed based on either the whole frames or the cropped patches, ignoring the fact that subjects can only access viewports. When watching 360° video, subjects select viewpor...

Twenty seconds of visual behaviour on social media gives insight into personality.

Scientific reports
Eye tracking allows the researcher to capture individual differences in the expression of visual exploration behaviour, which in certain contexts has been found to reflect aspects of the user's preferences and personality. In a novel approach, we rec...

Vision-Based Driver's Cognitive Load Classification Considering Eye Movement Using Machine Learning and Deep Learning.

Sensors (Basel, Switzerland)
Due to the advancement of science and technology, modern cars are highly technical, more activity occurs inside the car and driving is faster; however, statistics show that the number of road fatalities have increased in recent years because of drive...

Human-Machine Interface: Multiclass Classification by Machine Learning on 1D EOG Signals for the Control of an Omnidirectional Robot.

Sensors (Basel, Switzerland)
People with severe disabilities require assistance to perform their routine activities; a Human-Machine Interface (HMI) will allow them to activate devices that respond according to their needs. In this work, an HMI based on electrooculography (EOG) ...

Eye-Movement-Controlled Wheelchair Based on Flexible Hydrogel Biosensor and WT-SVM.

Biosensors
To assist patients with restricted mobility to control wheelchair freely, this paper presents an eye-movement-controlled wheelchair prototype based on a flexible hydrogel biosensor and Wavelet Transform-Support Vector Machine (WT-SVM) algorithm. Cons...

Towards Robust Robot Control in Cartesian Space Using an Infrastructureless Head- and Eye-Gaze Interface.

Sensors (Basel, Switzerland)
This paper presents a lightweight, infrastructureless head-worn interface for robust and real-time robot control in Cartesian space using head- and eye-gaze. The interface comes at a total weight of just 162 g. It combines a state-of-the-art visual s...