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Emotion Variation from Controlling Contrast of Visual Contents through EEG-Based Deep Emotion Recognition

Visual contents such as movies and animation evoke various human emotions. We examine an argument that the emotion from the visual contents may vary according to the contrast control of the scenes contained in the contents. We sample three emotions including positive, neutral and negative to prove o...

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Detalles Bibliográficos
Autores principales: Yang, Heekyung, Han, Jongdae, Min, Kyungha
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7472638/
https://www.ncbi.nlm.nih.gov/pubmed/32823741
http://dx.doi.org/10.3390/s20164543
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author Yang, Heekyung
Han, Jongdae
Min, Kyungha
author_facet Yang, Heekyung
Han, Jongdae
Min, Kyungha
author_sort Yang, Heekyung
collection PubMed
description Visual contents such as movies and animation evoke various human emotions. We examine an argument that the emotion from the visual contents may vary according to the contrast control of the scenes contained in the contents. We sample three emotions including positive, neutral and negative to prove our argument. We also sample several scenes of these emotions from visual contents and control the contrast of the scenes. We manipulate the contrast of the scenes and measure the change of valence and arousal from human participants who watch the contents using a deep emotion recognition module based on electroencephalography (EEG) signals. As a result, we conclude that the enhancement of contrast induces the increase of valence, while the reduction of contrast induces the decrease. Meanwhile, the contrast control affects arousal on a very minute scale.
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spelling pubmed-74726382020-09-17 Emotion Variation from Controlling Contrast of Visual Contents through EEG-Based Deep Emotion Recognition Yang, Heekyung Han, Jongdae Min, Kyungha Sensors (Basel) Article Visual contents such as movies and animation evoke various human emotions. We examine an argument that the emotion from the visual contents may vary according to the contrast control of the scenes contained in the contents. We sample three emotions including positive, neutral and negative to prove our argument. We also sample several scenes of these emotions from visual contents and control the contrast of the scenes. We manipulate the contrast of the scenes and measure the change of valence and arousal from human participants who watch the contents using a deep emotion recognition module based on electroencephalography (EEG) signals. As a result, we conclude that the enhancement of contrast induces the increase of valence, while the reduction of contrast induces the decrease. Meanwhile, the contrast control affects arousal on a very minute scale. MDPI 2020-08-13 /pmc/articles/PMC7472638/ /pubmed/32823741 http://dx.doi.org/10.3390/s20164543 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Yang, Heekyung
Han, Jongdae
Min, Kyungha
Emotion Variation from Controlling Contrast of Visual Contents through EEG-Based Deep Emotion Recognition
title Emotion Variation from Controlling Contrast of Visual Contents through EEG-Based Deep Emotion Recognition
title_full Emotion Variation from Controlling Contrast of Visual Contents through EEG-Based Deep Emotion Recognition
title_fullStr Emotion Variation from Controlling Contrast of Visual Contents through EEG-Based Deep Emotion Recognition
title_full_unstemmed Emotion Variation from Controlling Contrast of Visual Contents through EEG-Based Deep Emotion Recognition
title_short Emotion Variation from Controlling Contrast of Visual Contents through EEG-Based Deep Emotion Recognition
title_sort emotion variation from controlling contrast of visual contents through eeg-based deep emotion recognition
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7472638/
https://www.ncbi.nlm.nih.gov/pubmed/32823741
http://dx.doi.org/10.3390/s20164543
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