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The Perception of Naturalness Correlates with Low-Level Visual Features of Environmental Scenes

Previous research has shown that interacting with natural environments vs. more urban or built environments can have salubrious psychological effects, such as improvements in attention and memory. Even viewing pictures of nature vs. pictures of built environments can produce similar effects. A major...

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Autores principales: Berman, Marc G., Hout, Michael C., Kardan, Omid, Hunter, MaryCarol R., Yourganov, Grigori, Henderson, John M., Hanayik, Taylor, Karimi, Hossein, Jonides, John
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4273965/
https://www.ncbi.nlm.nih.gov/pubmed/25531411
http://dx.doi.org/10.1371/journal.pone.0114572
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author Berman, Marc G.
Hout, Michael C.
Kardan, Omid
Hunter, MaryCarol R.
Yourganov, Grigori
Henderson, John M.
Hanayik, Taylor
Karimi, Hossein
Jonides, John
author_facet Berman, Marc G.
Hout, Michael C.
Kardan, Omid
Hunter, MaryCarol R.
Yourganov, Grigori
Henderson, John M.
Hanayik, Taylor
Karimi, Hossein
Jonides, John
author_sort Berman, Marc G.
collection PubMed
description Previous research has shown that interacting with natural environments vs. more urban or built environments can have salubrious psychological effects, such as improvements in attention and memory. Even viewing pictures of nature vs. pictures of built environments can produce similar effects. A major question is: What is it about natural environments that produces these benefits? Problematically, there are many differing qualities between natural and urban environments, making it difficult to narrow down the dimensions of nature that may lead to these benefits. In this study, we set out to uncover visual features that related to individuals' perceptions of naturalness in images. We quantified naturalness in two ways: first, implicitly using a multidimensional scaling analysis and second, explicitly with direct naturalness ratings. Features that seemed most related to perceptions of naturalness were related to the density of contrast changes in the scene, the density of straight lines in the scene, the average color saturation in the scene and the average hue diversity in the scene. We then trained a machine-learning algorithm to predict whether a scene was perceived as being natural or not based on these low-level visual features and we could do so with 81% accuracy. As such we were able to reliably predict subjective perceptions of naturalness with objective low-level visual features. Our results can be used in future studies to determine if these features, which are related to naturalness, may also lead to the benefits attained from interacting with nature.
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spelling pubmed-42739652014-12-31 The Perception of Naturalness Correlates with Low-Level Visual Features of Environmental Scenes Berman, Marc G. Hout, Michael C. Kardan, Omid Hunter, MaryCarol R. Yourganov, Grigori Henderson, John M. Hanayik, Taylor Karimi, Hossein Jonides, John PLoS One Research Article Previous research has shown that interacting with natural environments vs. more urban or built environments can have salubrious psychological effects, such as improvements in attention and memory. Even viewing pictures of nature vs. pictures of built environments can produce similar effects. A major question is: What is it about natural environments that produces these benefits? Problematically, there are many differing qualities between natural and urban environments, making it difficult to narrow down the dimensions of nature that may lead to these benefits. In this study, we set out to uncover visual features that related to individuals' perceptions of naturalness in images. We quantified naturalness in two ways: first, implicitly using a multidimensional scaling analysis and second, explicitly with direct naturalness ratings. Features that seemed most related to perceptions of naturalness were related to the density of contrast changes in the scene, the density of straight lines in the scene, the average color saturation in the scene and the average hue diversity in the scene. We then trained a machine-learning algorithm to predict whether a scene was perceived as being natural or not based on these low-level visual features and we could do so with 81% accuracy. As such we were able to reliably predict subjective perceptions of naturalness with objective low-level visual features. Our results can be used in future studies to determine if these features, which are related to naturalness, may also lead to the benefits attained from interacting with nature. Public Library of Science 2014-12-22 /pmc/articles/PMC4273965/ /pubmed/25531411 http://dx.doi.org/10.1371/journal.pone.0114572 Text en © 2014 Berman et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Berman, Marc G.
Hout, Michael C.
Kardan, Omid
Hunter, MaryCarol R.
Yourganov, Grigori
Henderson, John M.
Hanayik, Taylor
Karimi, Hossein
Jonides, John
The Perception of Naturalness Correlates with Low-Level Visual Features of Environmental Scenes
title The Perception of Naturalness Correlates with Low-Level Visual Features of Environmental Scenes
title_full The Perception of Naturalness Correlates with Low-Level Visual Features of Environmental Scenes
title_fullStr The Perception of Naturalness Correlates with Low-Level Visual Features of Environmental Scenes
title_full_unstemmed The Perception of Naturalness Correlates with Low-Level Visual Features of Environmental Scenes
title_short The Perception of Naturalness Correlates with Low-Level Visual Features of Environmental Scenes
title_sort perception of naturalness correlates with low-level visual features of environmental scenes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4273965/
https://www.ncbi.nlm.nih.gov/pubmed/25531411
http://dx.doi.org/10.1371/journal.pone.0114572
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