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  An extensive dataset of eye movements during viewing of complex images

Wilming, N., Onat, S., Ossandón, J. P., Açık, A., Kietzmann, T. C., Kaspar, K., et al. (2017). An extensive dataset of eye movements during viewing of complex images. Scientific data, 4: 160126. doi:10.1038/sdata.2016.126.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-002D-2633-5 Version Permalink: https://hdl.handle.net/21.11116/0000-000C-8679-5
Genre: Journal Article

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Wilming_2016_DataDescriptor.pdf (Publisher version), 2MB
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https://hdl.handle.net/21.11116/0000-000C-867A-4
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Wilming_2016_DataDescriptor.pdf
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Copyright Date:
2017
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Copyright © The Author(s) 2017
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http://creativecommons.org/licenses/by/3.0/

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https://www.nature.com/articles/sdata2016126 (Publisher version)
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 Creators:
Wilming, Niklas, Author
Onat, Selim, Author
Ossandón, José P., Author
Açık, Alper, Author
Kietzmann, Tim C., Author
Kaspar, Kai, Author
Gameiro, Ricardo R., Author
Vormberg, Alexandra1, Author
König, Peter, Author
Affiliations:
1Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Max Planck Society, Deutschordenstr. 46, 60528 Frankfurt, DE, ou_2074314              

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 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 Osnabruck 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.

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 Dates: 2017-01-31
 Publication Status: Published online
 Pages: -
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 Rev. Type: Peer
 Identifiers: DOI: 10.1038/sdata.2016.126
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Title: Scientific data
  Alternative Title : Scientific data
Source Genre: Journal
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Pages: - Volume / Issue: 4 Sequence Number: 160126 Start / End Page: - Identifier: ISBN: 2052-4463 (Electronic)2052-4463 (Linking)