AIMC Topic: Eye Movements

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Using machine learning to detect events in eye-tracking data.

Behavior research methods
Event detection is a challenging stage in eye movement data analysis. A major drawback of current event detection methods is that parameters have to be adjusted based on eye movement data quality. Here we show that a fully automated classification of...

A parametric texture model based on deep convolutional features closely matches texture appearance for humans.

Journal of vision
Our visual environment is full of texture-"stuff" like cloth, bark, or gravel as distinct from "things" like dresses, trees, or paths-and humans are adept at perceiving subtle variations in material properties. To investigate image features important...

Towards free 3D end-point control for robotic-assisted human reaching using binocular eye tracking.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
Eye-movements are the only directly observable behavioural signals that are highly correlated with actions at the task level, and proactive of body movements and thus reflect action intentions. Moreover, eye movements are preserved in many movement d...

Using support vector machines to identify literacy skills: Evidence from eye movements.

Behavior research methods
Is inferring readers' literacy skills possible by analyzing their eye movements during text reading? This study used Support Vector Machines (SVM) to analyze eye movement data from 61 undergraduate students who read a multiple-paragraph, multiple-top...

Can Robotic Interaction Improve Joint Attention Skills?

Journal of autism and developmental disorders
Although it has often been argued that clinical applications of advanced technology may hold promise for addressing impairments associated with autism spectrum disorder (ASD), relatively few investigations have indexed the impact of intervention and ...

Actions in the Eye: Dynamic Gaze Datasets and Learnt Saliency Models for Visual Recognition.

IEEE transactions on pattern analysis and machine intelligence
Systems based on bag-of-words models from image features collected at maxima of sparse interest point operators have been used successfully for both computer visual object and action recognition tasks. While the sparse, interest-point based approach ...