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Development of video-based emotion recognition using deep learning with Google colab

Emotion recognition using images, videos, or speech as input is considered as a hot topic in the field of research over some years. With the introduction of deep learning techniques, e.g., convolutional neural networks (CNN), applied in emotion recognition, has produced promising results. Human fac...

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Main Authors: Gunawan, Teddy Surya, Ashraf, Arselan, Riza, Bob Subhan, Haryanto, Edy Victor, Rosnelly, Rika, Kartiwi, Mira, Janin, Zuriati
Format: Article
Language:English
English
Published: UAD 2020
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices
Online Access:http://irep.iium.edu.my/82532/7/82532_Development%20of%20video-based%20emotion%20recognition.pdf
http://irep.iium.edu.my/82532/8/82532_Development%20of%20video-based%20emotion%20recognition_Scopus.pdf
http://irep.iium.edu.my/82532/
http://journal.uad.ac.id/index.php/TELKOMNIKA
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spelling my.iium.irep.825322021-02-11T06:55:57Z http://irep.iium.edu.my/82532/ Development of video-based emotion recognition using deep learning with Google colab Gunawan, Teddy Surya Ashraf, Arselan Riza, Bob Subhan Haryanto, Edy Victor Rosnelly, Rika Kartiwi, Mira Janin, Zuriati TK Electrical engineering. Electronics Nuclear engineering TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices Emotion recognition using images, videos, or speech as input is considered as a hot topic in the field of research over some years. With the introduction of deep learning techniques, e.g., convolutional neural networks (CNN), applied in emotion recognition, has produced promising results. Human facial expressions are considered as critical components in understanding one's emotions. This paper sheds light on recognizing the emotions using deep learning techniques from the videos. The methodology of the recognition process, along with its description, is provided in this paper. Some of the video-based datasets used in many scholarly works are also examined. Results obtained from different emotion recognition models are presented along with their performance parameters. An experiment was carried out on the fer2013 dataset in Google Colab for depression detection, which came out to be 97% accurate on the training set and 57.4% accurate on the testing set. UAD 2020-10 Article PeerReviewed application/pdf en http://irep.iium.edu.my/82532/7/82532_Development%20of%20video-based%20emotion%20recognition.pdf application/pdf en http://irep.iium.edu.my/82532/8/82532_Development%20of%20video-based%20emotion%20recognition_Scopus.pdf Gunawan, Teddy Surya and Ashraf, Arselan and Riza, Bob Subhan and Haryanto, Edy Victor and Rosnelly, Rika and Kartiwi, Mira and Janin, Zuriati (2020) Development of video-based emotion recognition using deep learning with Google colab. Telkomnika, 18 (5). pp. 2463-2471. ISSN 1693-6930 http://journal.uad.ac.id/index.php/TELKOMNIKA 10.12928/telkomnika.v18i5.16717
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
English
topic TK Electrical engineering. Electronics Nuclear engineering
TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices
Gunawan, Teddy Surya
Ashraf, Arselan
Riza, Bob Subhan
Haryanto, Edy Victor
Rosnelly, Rika
Kartiwi, Mira
Janin, Zuriati
Development of video-based emotion recognition using deep learning with Google colab
description Emotion recognition using images, videos, or speech as input is considered as a hot topic in the field of research over some years. With the introduction of deep learning techniques, e.g., convolutional neural networks (CNN), applied in emotion recognition, has produced promising results. Human facial expressions are considered as critical components in understanding one's emotions. This paper sheds light on recognizing the emotions using deep learning techniques from the videos. The methodology of the recognition process, along with its description, is provided in this paper. Some of the video-based datasets used in many scholarly works are also examined. Results obtained from different emotion recognition models are presented along with their performance parameters. An experiment was carried out on the fer2013 dataset in Google Colab for depression detection, which came out to be 97% accurate on the training set and 57.4% accurate on the testing set.
format Article
author Gunawan, Teddy Surya
Ashraf, Arselan
Riza, Bob Subhan
Haryanto, Edy Victor
Rosnelly, Rika
Kartiwi, Mira
Janin, Zuriati
author_facet Gunawan, Teddy Surya
Ashraf, Arselan
Riza, Bob Subhan
Haryanto, Edy Victor
Rosnelly, Rika
Kartiwi, Mira
Janin, Zuriati
author_sort Gunawan, Teddy Surya
title Development of video-based emotion recognition using deep learning with Google colab
title_short Development of video-based emotion recognition using deep learning with Google colab
title_full Development of video-based emotion recognition using deep learning with Google colab
title_fullStr Development of video-based emotion recognition using deep learning with Google colab
title_full_unstemmed Development of video-based emotion recognition using deep learning with Google colab
title_sort development of video-based emotion recognition using deep learning with google colab
publisher UAD
publishDate 2020
url http://irep.iium.edu.my/82532/7/82532_Development%20of%20video-based%20emotion%20recognition.pdf
http://irep.iium.edu.my/82532/8/82532_Development%20of%20video-based%20emotion%20recognition_Scopus.pdf
http://irep.iium.edu.my/82532/
http://journal.uad.ac.id/index.php/TELKOMNIKA
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score 13.211869

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