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Differentiating aggregate gaze distributions

Proceedings of the ACM SIGGRAPH Symposium on Applied Perception in Graphics and Visualization, 2011
A machine learning approach used to classify aggregate gaze distributions recorded by an eye tracker and visualized as heatmaps is demonstrated to successfully discriminate between free and task-driven exploration of video clips.
Thomas Grindinger   +2 more
semanticscholar   +2 more sources

Information Constrained Control Analysis of Eye Gaze Distribution Under Workload

IEEE Transactions on Human-Machine Systems, 2019
We describe a novel model of human eye gaze behavior under workload, derived from the basic principle of information constrained control. The model assumes two distributions over the visual field: A saliency distribution, which is nongoal oriented, and a
Ron M. Hecht   +4 more
semanticscholar   +2 more sources

Gaze step distributions reflect fixations and saccades: a comment on.

Cognition, 2012
In three experimental tasks Stephen and Mirman (2010) measured gaze steps, the distance in pixels between gaze positions on successive samples from an eyetracker. They argued that the distribution of gaze steps is best fit by the lognormal distribution, and based on this analysis they concluded that interactive cognitive processes underlie eye movement
R. Bogartz, A. Staub
semanticscholar   +3 more sources

Evaluation of Gaze-to-Object Mapping Algorithms for Use in "Real-World" Translatable Neuropsychological Paradigms.

Psychology and Neuroscience, 2023
Objective Eye-tracking technology is commonly used for identifying objects of visual attention. However, applying this technology to virtual reality (VR) applications is challenging.
Weichen Liu   +3 more
semanticscholar   +1 more source

Model-driven Simulation of Eye Gaze Dynamics in Standard Visual Cognitive Assessments

International Conference on Agents, 2023
The increasing popularity of wearable eye-tracking systems has led to growing interest in monitoring and predicting mental disorders and dementia in mobile health (m-health) applications.
Kevin Hung   +5 more
semanticscholar   +1 more source

Gender Classification using the Gaze Distributions of Observers on Privacy-protected Training Images

VISIGRAPP, 2020
: We propose a method for classifying the gender of pedestrians using a classifier trained by images containing privacy-protection of the head region. Recently, manipulated training images containing pedestrians have been required to protect the privacy ...
Michiko Inoue   +2 more
semanticscholar   +1 more source

V-ir-Net: A Novel Neural Network for Pupil and Corneal Reflection Detection trained on Simulated Light Distributions

International Conference on Human-Computer Interaction with Mobile Devices and Services, 2023
Deep learning has shown promise for gaze estimation in Virtual Reality (VR) and other head-mounted applications, but such models are hard to train due to lack of available data.
Virmarie Maquiling   +4 more
semanticscholar   +1 more source

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