Publication: An extensive dataset of eye movements during viewing of complex images
dc.contributor.author | Wilming, N. | |
dc.contributor.author | Onat, S. | |
dc.contributor.author | Ossandón, J. P. | |
dc.contributor.author | Açık, Alper | |
dc.contributor.author | Kietzmann, T.C | |
dc.contributor.author | Kaspar, K. | |
dc.contributor.author | Gameiro, R. R. | |
dc.contributor.author | Vormberg, A. | |
dc.contributor.author | König, P. | |
dc.contributor.department | Psychology | |
dc.contributor.ozuauthor | AÇIK, Alper | |
dc.date.accessioned | 2017-02-02T06:20:31Z | |
dc.date.available | 2017-02-02T06:20:31Z | |
dc.date.issued | 2017 | |
dc.description.abstract | We present a dataset of free-viewing eye-movement recordings that contains more than 2.7 million fixation locations from 949 observers on more than 1000 images from different categories. This dataset aggregates and harmonizes data from 23 different studies conducted at the Institute of Cognitive Science at Osnabrück University and the University Medical Center in Hamburg-Eppendorf. Trained personnel recorded all studies under standard conditions with homogeneous equipment and parameter settings. All studies allowed for free eye-movements, and differed in the age range of participants (~7–80 years), stimulus sizes, stimulus modifications (phase scrambled, spatial filtering, mirrored), and stimuli categories (natural and urban scenes, web sites, fractal, pink-noise, and ambiguous artistic figures). The size and variability of viewing behavior within this dataset presents a strong opportunity for evaluating and comparing computational models of overt attention, and furthermore, for thoroughly quantifying strategies of viewing behavior. This also makes the dataset a good starting point for investigating whether viewing strategies change in patient groups. | en_US |
dc.description.sponsorship | European Research Council | |
dc.identifier.doi | 10.1038/sdata.2016.126 | en_US |
dc.identifier.scopus | 2-s2.0-85011268677 | |
dc.identifier.uri | http://hdl.handle.net/10679/4763 | |
dc.identifier.uri | https://doi.org/10.1038/sdata.2016.126 | |
dc.identifier.wos | 000392954500001 | |
dc.language.iso | eng | en_US |
dc.peerreviewed | yes | en_US |
dc.publicationstatus | published | en_US |
dc.publisher | Nature | en_US |
dc.relation.ispartof | Scientific Data | en_US |
dc.relation.publicationcategory | International Refereed Journal | |
dc.rights | info:eu-repo/semantics/openAccess | |
dc.subject.keywords | Attention | en_US |
dc.subject.keywords | Computational neuroscience | en_US |
dc.title | An extensive dataset of eye movements during viewing of complex images | en_US |
dc.type | Article | en_US |
dspace.entity.type | Publication | |
relation.isOrgUnitOfPublication | eb613b06-2aad-4fc0-baba-a9a816d9132e | |
relation.isOrgUnitOfPublication.latestForDiscovery | eb613b06-2aad-4fc0-baba-a9a816d9132e |
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