This dataset contrains the behavioural and eyetracking data for the paper: Stewart, E.E.M., Ludwig, C.J.H. & Schütz, A.C. Humans represent the precision and utility of information acquired across fixations. Sci Rep 12, 2411 (2022). https://doi.org/10.1038/s41598-022-06357-7 For results of the supplementary online experiment for this paper, as well as analysis of the images in the Amsterdam Library of Object Images (ALOI) dataset, please see the separate dataset: https://doi.org/10.5281/zenodo.6068096 This dataset also contrains a copy of the ALOI images used in the experiment, originally sourced from https://aloi.science.uva.nl/
Most bottom-up models that predict human eye fixations are based on contrast features. The saliency ...
Saliency maps produced by different algorithms are often evaluated by comparing output to fixated im...
In the course of running an eye tracking experiment, one computer system or subsystem typically pre...
This repository contains the coder settings and event-based agreement score algorithms used and deve...
This repository contains the coder settings and event-based agreement score algorithms used and deve...
The following dataset supplements the publication Veto, Peter & Uhlig, Marvin & Troje, Nikolaus F.,...
Saliency maps produced by different algorithms are often evaluated by comparing output to fixated im...
Models of fixation selection are a central tool in the quest to understand how the human mind select...
<p>Stimuli used for Dataset 1 in</p> <p>Mathot, Siebold, Donk, and Vitu (in prep). <em>Large Pupils ...
This repository contains the coder settings and event-based agreement score algorithms used and deve...
This paper presents the results of a computational experiment designed to investigate the extent to ...
Decision researchers frequently analyze attention to individual objects to test hypotheses about und...
This is the data from: Niels A. Kloosterman, Jan Willem de Gee, Markus Werkle-Bergner, Ulman Lindenb...
Fixation datasets are commonly used for machine learning. By studying how humans actually look at ob...
Interest point detectors (e.g. SIFT, SURF, and MSER) have been successfully applied to numerous appl...
Most bottom-up models that predict human eye fixations are based on contrast features. The saliency ...
Saliency maps produced by different algorithms are often evaluated by comparing output to fixated im...
In the course of running an eye tracking experiment, one computer system or subsystem typically pre...
This repository contains the coder settings and event-based agreement score algorithms used and deve...
This repository contains the coder settings and event-based agreement score algorithms used and deve...
The following dataset supplements the publication Veto, Peter & Uhlig, Marvin & Troje, Nikolaus F.,...
Saliency maps produced by different algorithms are often evaluated by comparing output to fixated im...
Models of fixation selection are a central tool in the quest to understand how the human mind select...
<p>Stimuli used for Dataset 1 in</p> <p>Mathot, Siebold, Donk, and Vitu (in prep). <em>Large Pupils ...
This repository contains the coder settings and event-based agreement score algorithms used and deve...
This paper presents the results of a computational experiment designed to investigate the extent to ...
Decision researchers frequently analyze attention to individual objects to test hypotheses about und...
This is the data from: Niels A. Kloosterman, Jan Willem de Gee, Markus Werkle-Bergner, Ulman Lindenb...
Fixation datasets are commonly used for machine learning. By studying how humans actually look at ob...
Interest point detectors (e.g. SIFT, SURF, and MSER) have been successfully applied to numerous appl...
Most bottom-up models that predict human eye fixations are based on contrast features. The saliency ...
Saliency maps produced by different algorithms are often evaluated by comparing output to fixated im...
In the course of running an eye tracking experiment, one computer system or subsystem typically pre...