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Recognition of Emotion According to the Physical Elements of the Video

The increasing interest in the effects of emotion on cognitive, social, and neural processes creates a constant need for efficient and reliable techniques for emotion elicitation. Emotions are important in many areas, especially in advertising design and video production. The impact of emotions on t...

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Detalles Bibliográficos
Autores principales: Zhang, Jing, Wen, Xingyu, Whang, Mincheol
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7038227/
https://www.ncbi.nlm.nih.gov/pubmed/31991587
http://dx.doi.org/10.3390/s20030649
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author Zhang, Jing
Wen, Xingyu
Whang, Mincheol
author_facet Zhang, Jing
Wen, Xingyu
Whang, Mincheol
author_sort Zhang, Jing
collection PubMed
description The increasing interest in the effects of emotion on cognitive, social, and neural processes creates a constant need for efficient and reliable techniques for emotion elicitation. Emotions are important in many areas, especially in advertising design and video production. The impact of emotions on the audience plays an important role. This paper analyzes the physical elements in a two-dimensional emotion map by extracting the physical elements of a video (color, light intensity, sound, etc.). We used k-nearest neighbors (K-NN), support vector machine (SVM), and multilayer perceptron (MLP) classifiers in the machine learning method to accurately predict the four dimensions that express emotions, as well as summarize the relationship between the two-dimensional emotion space and physical elements when designing and producing video.
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spelling pubmed-70382272020-03-09 Recognition of Emotion According to the Physical Elements of the Video Zhang, Jing Wen, Xingyu Whang, Mincheol Sensors (Basel) Article The increasing interest in the effects of emotion on cognitive, social, and neural processes creates a constant need for efficient and reliable techniques for emotion elicitation. Emotions are important in many areas, especially in advertising design and video production. The impact of emotions on the audience plays an important role. This paper analyzes the physical elements in a two-dimensional emotion map by extracting the physical elements of a video (color, light intensity, sound, etc.). We used k-nearest neighbors (K-NN), support vector machine (SVM), and multilayer perceptron (MLP) classifiers in the machine learning method to accurately predict the four dimensions that express emotions, as well as summarize the relationship between the two-dimensional emotion space and physical elements when designing and producing video. MDPI 2020-01-24 /pmc/articles/PMC7038227/ /pubmed/31991587 http://dx.doi.org/10.3390/s20030649 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
Zhang, Jing
Wen, Xingyu
Whang, Mincheol
Recognition of Emotion According to the Physical Elements of the Video
title Recognition of Emotion According to the Physical Elements of the Video
title_full Recognition of Emotion According to the Physical Elements of the Video
title_fullStr Recognition of Emotion According to the Physical Elements of the Video
title_full_unstemmed Recognition of Emotion According to the Physical Elements of the Video
title_short Recognition of Emotion According to the Physical Elements of the Video
title_sort recognition of emotion according to the physical elements of the video
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7038227/
https://www.ncbi.nlm.nih.gov/pubmed/31991587
http://dx.doi.org/10.3390/s20030649
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AT wenxingyu recognitionofemotionaccordingtothephysicalelementsofthevideo
AT whangmincheol recognitionofemotionaccordingtothephysicalelementsofthevideo