AIMC Topic: Eye Movements

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Under-exploration of Three-Dimensional Images Leads to Search Errors for Small Salient Targets.

Current biology : CB
Advances in 3D imaging technology are transforming how radiologists search for cancer and how security officers scrutinize baggage for dangerous objects. These new 3D technologies often improve search over 2D images but vastly increase the image data...

Performance Analysis of a Head and Eye Motion-Based Control Interface for Assistive Robots.

Sensors (Basel, Switzerland)
Assistive robots support people with limited mobility in their everyday life activities and work. However, most of the assistive systems and technologies for supporting eating and drinking require a residual mobility in arms or hands. For people with...

Gravitational Laws of Focus of Attention.

IEEE transactions on pattern analysis and machine intelligence
The understanding of the mechanisms behind focus of attention in a visual scene is a problem of great interest in visual perception and computer vision. In this paper, we describe a model of scanpath as a dynamic process which can be interpreted as a...

Accurate detection of cerebellar smooth pursuit eye movement abnormalities via mobile phone video and machine learning.

Scientific reports
Eye movements are disrupted in many neurodegenerative diseases and are frequent and early features in conditions affecting the cerebellum. Characterizing eye movements is important for diagnosis and may be useful for tracking disease progression and ...

Population coding in the cerebellum: a machine learning perspective.

Journal of neurophysiology
The cere resembles a feedforward, three-layer network of neurons in which the "hidden layer" consists of Purkinje cells (P-cells) and the output layer consists of deep cerebellar nucleus (DCN) neurons. In this analogy, the output of each DCN neuron i...

Meaning maps and saliency models based on deep convolutional neural networks are insensitive to image meaning when predicting human fixations.

Cognition
Eye movements are vital for human vision, and it is therefore important to understand how observers decide where to look. Meaning maps (MMs), a technique to capture the distribution of semantic information across an image, have recently been proposed...

Eye-Tracking Analysis for Emotion Recognition.

Computational intelligence and neuroscience
This article reports the results of the study related to emotion recognition by using eye-tracking. Emotions were evoked by presenting a dynamic movie material in the form of 21 video fragments. Eye-tracking signals recorded from 30 participants were...

Computational discrimination between natural images based on gaze during mental imagery.

Scientific reports
When retrieving image from memory, humans usually move their eyes spontaneously as if the image were in front of them. Such eye movements correlate strongly with the spatial layout of the recalled image content and function as memory cues facilitatin...

Evaluation of mental workload during automobile driving using one-class support vector machine with eye movement data.

Applied ergonomics
The aim of this study is to investigate the usefulness of the anomaly detection method by one-class support vector machine (OCSVM) for the evaluation of mental workload (MWL) during automobile driving. Twelve students (six males and six females) part...

A Modeling Study of the Emergence of Eye Position Gain Fields Modulating the Responses of Visual Neurons in the Brain.

Frontiers in neural circuits
The responses of many cortical neurons to visual stimuli are modulated by the position of the eye. This form of gain modulation by eye position does not change the retinotopic selectivity of the responses, but only changes the amplitude of the respon...